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Available online ,
doi: 10.11999/JEIT230815
Abstract:
In the research on utilizing emerging non-volatile storage arrays for in-memory computing, the latency of in-memory multipliers often exhibits exponential growth with increasing bit width, and significantly impacts the computational performance. A Voltage-Gated Spin-Orbit Torque Magnetoresistive Random-Acess Memory (VGSOT-MRAM) device unit crossbar array is proposed and a circuit design approach for in-memory Wallace tree multipliers is presented in this paper. The proposed series-connected storage unit structure effectively addresses the issue of low resistance values in magnetic storage units through resistive summing. Furthermore, an in-memory computing architecture based on a voltage-controlled spin-orbit torque magnetic storage unit crossbar array is introduced. Finally, a five-input majority decision logic gate implemented during the “read” operation is leveraged to further reduce the logic depth of the Wallace tree multiplier. Compared to existing multiplier design methods, the proposed approach reduces the delay overhead from O(n2) to O(log2 n), with even lower latency for larger bit widths.
In the research on utilizing emerging non-volatile storage arrays for in-memory computing, the latency of in-memory multipliers often exhibits exponential growth with increasing bit width, and significantly impacts the computational performance. A Voltage-Gated Spin-Orbit Torque Magnetoresistive Random-Acess Memory (VGSOT-MRAM) device unit crossbar array is proposed and a circuit design approach for in-memory Wallace tree multipliers is presented in this paper. The proposed series-connected storage unit structure effectively addresses the issue of low resistance values in magnetic storage units through resistive summing. Furthermore, an in-memory computing architecture based on a voltage-controlled spin-orbit torque magnetic storage unit crossbar array is introduced. Finally, a five-input majority decision logic gate implemented during the “read” operation is leveraged to further reduce the logic depth of the Wallace tree multiplier. Compared to existing multiplier design methods, the proposed approach reduces the delay overhead from O(n2) to O(log2 n), with even lower latency for larger bit widths.
Available online ,
doi: 10.11999/JEIT221479
Abstract:
The quasi-superdirective reradiation based on the magnetic dipole resonance occurring within a passive dielectric resonator is presented to augment the backscattering cross-section of thin conducting plates at edge-on incidence. It is demonstrated that a hybrid electromagnetic resonance mode reradiating like a magnetic dipole can be induced within a properly dimensioned cuboid dielectric under the illumination of a plane electromagnetic wave. Using this cuboid dielectric as a basic unit cell, a supercell consisting of two identical dielectrics closely cascaded along the propagation direction of the impinging wave is formed. It is observed that both the magnetic and electric fields induced within the two dielectrics of the supercell exhibit opposite senses along with almost equal magnitudes. Because of the internal field distribution with opposite phases and almost equal magnitudes, the supercell acts as a two-element quasi-superdirective magnetic dipole array and the resultant quasi-superdirective reradiation effectively contributes to the backscattering cross-section enhancement. Further, the supercells with halved profile are loaded onto the surfaces of thin conducting plates according to the image theory. The results indicate that the magnetic-dipole-based quasi-superdirective reradiation assisted by dielectric resonators with a profile of only 0.078λ0 noticeably modifies the edge-on scattering characteristic of thin conducting plates. Effective augmentation of backscattering cross-section for edge-on incidence is therefore achieved within relatively wide band and angular ranges.
The quasi-superdirective reradiation based on the magnetic dipole resonance occurring within a passive dielectric resonator is presented to augment the backscattering cross-section of thin conducting plates at edge-on incidence. It is demonstrated that a hybrid electromagnetic resonance mode reradiating like a magnetic dipole can be induced within a properly dimensioned cuboid dielectric under the illumination of a plane electromagnetic wave. Using this cuboid dielectric as a basic unit cell, a supercell consisting of two identical dielectrics closely cascaded along the propagation direction of the impinging wave is formed. It is observed that both the magnetic and electric fields induced within the two dielectrics of the supercell exhibit opposite senses along with almost equal magnitudes. Because of the internal field distribution with opposite phases and almost equal magnitudes, the supercell acts as a two-element quasi-superdirective magnetic dipole array and the resultant quasi-superdirective reradiation effectively contributes to the backscattering cross-section enhancement. Further, the supercells with halved profile are loaded onto the surfaces of thin conducting plates according to the image theory. The results indicate that the magnetic-dipole-based quasi-superdirective reradiation assisted by dielectric resonators with a profile of only 0.078λ0 noticeably modifies the edge-on scattering characteristic of thin conducting plates. Effective augmentation of backscattering cross-section for edge-on incidence is therefore achieved within relatively wide band and angular ranges.
Available online ,
doi: 10.11999/JEIT221593
Abstract:
RAIN is a lightweight block cipher with SPN structure, which not only has strong security, but also possesses high software and hardware implementation efficiency. Meet-in-the-middle attacks are widely used in the security analysis of block ciphers algorithms. In this paper, the meet-in-the-middle attack on RAIN is researched. By examining the structural characteristics and the properties of truncated differential of RAIN-128, both 4-round and 6-round meet-in-the-middle distinguishers are first constructed by using differential enumeration technique, and meet-in-the-middle attacks on 8-round and 10-round RAIN-128 are presented, respectively. For 8-round attack, in the preprocessing, the time complexity is\begin{document}$ {2^{68}} $\end{document} \begin{document}$ {2^{75}} $\end{document} \begin{document}$ {2^{109}} $\end{document} \begin{document}$ {2^{72}} $\end{document} \begin{document}$ {2^{214}} $\end{document} \begin{document}$ {2^{219}} $\end{document} \begin{document}$ {2^{109}} $\end{document} \begin{document}$ {2^{72}} $\end{document}
RAIN is a lightweight block cipher with SPN structure, which not only has strong security, but also possesses high software and hardware implementation efficiency. Meet-in-the-middle attacks are widely used in the security analysis of block ciphers algorithms. In this paper, the meet-in-the-middle attack on RAIN is researched. By examining the structural characteristics and the properties of truncated differential of RAIN-128, both 4-round and 6-round meet-in-the-middle distinguishers are first constructed by using differential enumeration technique, and meet-in-the-middle attacks on 8-round and 10-round RAIN-128 are presented, respectively. For 8-round attack, in the preprocessing, the time complexity is
Available online ,
doi: 10.11999/JEIT230426
Abstract:
To resolve the channel uncertainties, wireless information leakage and low communication quality caused by obstacles, a robust secure resource allocation algorithm for a Reconfigurable Intelligent Surface (RIS) aided Multiple Input Single Output (MISO) Symbiotic Radio (SR) network is proposed. Considering the constraint of the secure rate of the primary user, the constraint of the minimum rate of the secondary user and the constraint of the minimum harvested energy of the RIS, a resource allocation problem based on the bounded channel uncertainties is formulated by jointly optimizing the active beamforming vector and the passive beamforming vector. Then, the parameter perturbation included non-convex problem is transformed into a deterministic convex optimization problem via the semidefinite relaxation, S-procedure and the variable substitution methods, and a semidefinite relaxation based robust resource allocation algorithm is proposed. Numerical results verify that the proposed algorithm has better convergence and robustness compared with existing algorithms.
To resolve the channel uncertainties, wireless information leakage and low communication quality caused by obstacles, a robust secure resource allocation algorithm for a Reconfigurable Intelligent Surface (RIS) aided Multiple Input Single Output (MISO) Symbiotic Radio (SR) network is proposed. Considering the constraint of the secure rate of the primary user, the constraint of the minimum rate of the secondary user and the constraint of the minimum harvested energy of the RIS, a resource allocation problem based on the bounded channel uncertainties is formulated by jointly optimizing the active beamforming vector and the passive beamforming vector. Then, the parameter perturbation included non-convex problem is transformed into a deterministic convex optimization problem via the semidefinite relaxation, S-procedure and the variable substitution methods, and a semidefinite relaxation based robust resource allocation algorithm is proposed. Numerical results verify that the proposed algorithm has better convergence and robustness compared with existing algorithms.
Available online ,
doi: 10.11999/JEIT230208
Abstract:
As the basis of many intelligent visual tasks, Multi-Object Tracking (MOT) is a challenging problem in computer vision. Occlusion is a main factor affecting the tracking accuracy. To solve the occlusion problem, in this paper, the strategy of tracking-by-detection is adopted to obtain complete trajectories of targets based on associating tracklets. Meanwhile, to improve the tracking robustness, the tracklet generation problem is transformed into the facility location problem in operations research area and further a submodular optimization based tracklet generation method is proposed. In this method, two complementary features including Histogram of Oriented Gradient (HOG)and Color Name (CN) are integrated to describe the target appearance, and a weighting coefficient is also designed by motion information to improve the matching accuracy. At length, a submodular maximization algorithm with constraints is developed to achieve the global data association by selecting the targets to form the tracklets. By comparative experiments on the benchmark datasets, the proposed method can solve the occlusion problem effectively with guaranteed performance.
As the basis of many intelligent visual tasks, Multi-Object Tracking (MOT) is a challenging problem in computer vision. Occlusion is a main factor affecting the tracking accuracy. To solve the occlusion problem, in this paper, the strategy of tracking-by-detection is adopted to obtain complete trajectories of targets based on associating tracklets. Meanwhile, to improve the tracking robustness, the tracklet generation problem is transformed into the facility location problem in operations research area and further a submodular optimization based tracklet generation method is proposed. In this method, two complementary features including Histogram of Oriented Gradient (HOG)and Color Name (CN) are integrated to describe the target appearance, and a weighting coefficient is also designed by motion information to improve the matching accuracy. At length, a submodular maximization algorithm with constraints is developed to achieve the global data association by selecting the targets to form the tracklets. By comparative experiments on the benchmark datasets, the proposed method can solve the occlusion problem effectively with guaranteed performance.
Available online ,
doi: 10.11999/JEIT230012
Abstract:
With the feature size of CMOS device entering the nanoscale, the circuit failure issue caused by high-energy particle radiation is becoming more and more serious, which brings severe challenges to the circuit reliability. At present, it is urgent to accurately evaluate the reliability of the integrated circuit and reinforce the fault tolerance of circuit, so as to improve the reliability of the circuit system. However, due to the large number of fan-out reconvergence structures in the logic circuit, the resulting signal correlation causes difficulties in reliability evaluation and critical gates location. This paper proposes critical gates location algorithm for logic circuit based on correlation separation. First, the circuit is divided into multiple independent circuit structures (ICS); second, taking ICS as the basic unit to analyze fault propagation and signal correlation; Then, the circuit module after correlation separation and the reverse search algorithm is used to accurately locate the circuit critical gates; Finally, critical gates location and targeted fault tolerance reinforcement for the input vector space are comprehensively considered. The experimental results show that proposed algorithm can accurately and efficiently locate the critical gates of logic circuit, and it is suitable for reliability evaluation and efficient fault-tolerant design of large-scale and super-scale circuits.
With the feature size of CMOS device entering the nanoscale, the circuit failure issue caused by high-energy particle radiation is becoming more and more serious, which brings severe challenges to the circuit reliability. At present, it is urgent to accurately evaluate the reliability of the integrated circuit and reinforce the fault tolerance of circuit, so as to improve the reliability of the circuit system. However, due to the large number of fan-out reconvergence structures in the logic circuit, the resulting signal correlation causes difficulties in reliability evaluation and critical gates location. This paper proposes critical gates location algorithm for logic circuit based on correlation separation. First, the circuit is divided into multiple independent circuit structures (ICS); second, taking ICS as the basic unit to analyze fault propagation and signal correlation; Then, the circuit module after correlation separation and the reverse search algorithm is used to accurately locate the circuit critical gates; Finally, critical gates location and targeted fault tolerance reinforcement for the input vector space are comprehensively considered. The experimental results show that proposed algorithm can accurately and efficiently locate the critical gates of logic circuit, and it is suitable for reliability evaluation and efficient fault-tolerant design of large-scale and super-scale circuits.
Available online ,
doi: 10.11999/JEIT240000
Abstract:
The electronics and technology area in Division I of Information Science Department of National Natural Science Foundation of China covers the research fields of electrical circuits and systems, electromagnetic fields and waves, electronics and applications. This report introduces the application and funding statistics of several types of projects that are classified into two talent and exploratory funding categories. The analysis is from various aspects, including application codes, age of applicants, host institutions and the trend in recent five years. It aims to provide a general guidance for the scientific researchers about the hot topics and future development directions in this area.
The electronics and technology area in Division I of Information Science Department of National Natural Science Foundation of China covers the research fields of electrical circuits and systems, electromagnetic fields and waves, electronics and applications. This report introduces the application and funding statistics of several types of projects that are classified into two talent and exploratory funding categories. The analysis is from various aspects, including application codes, age of applicants, host institutions and the trend in recent five years. It aims to provide a general guidance for the scientific researchers about the hot topics and future development directions in this area.
Available online ,
doi: 10.11999/JEIT221097
Abstract:
A 2-dimension compressed sensing algorithm based on adaptive blocking and joint optimization Smooth l0 (SL0) norm is proposed to solve the problem of poor compression and reconstruction performance of the traditional compressed sensing model and reconstruction method. In the compression process, gray entropy and quadtree algorithm are used for adaptive blocking and sample rate allocation. At the same time, the compressed sensing model is optimized and the chaotic cyclic matrix is used as the measure matrix, which improves the compression performance. In the reconstruction process based on SL0 algorithm, a fitting function with higher steepness and a scheme combined with Quasi-Newton method and dynamic iteration are adopted to improve the reconstruction quality and efficiency. Compared with other algorithms, the peak signal to noise ratio and structural similarity index of the proposed algorithm are improved by 5.44 dB and 21.08% on average respectively. The average calculation time is only 1.59 s. Based on realizing image compression and accurate reconstruction stably and quickly, the proposed algorithm provides a new method for compressed sensing and image reconstruction.
A 2-dimension compressed sensing algorithm based on adaptive blocking and joint optimization Smooth l0 (SL0) norm is proposed to solve the problem of poor compression and reconstruction performance of the traditional compressed sensing model and reconstruction method. In the compression process, gray entropy and quadtree algorithm are used for adaptive blocking and sample rate allocation. At the same time, the compressed sensing model is optimized and the chaotic cyclic matrix is used as the measure matrix, which improves the compression performance. In the reconstruction process based on SL0 algorithm, a fitting function with higher steepness and a scheme combined with Quasi-Newton method and dynamic iteration are adopted to improve the reconstruction quality and efficiency. Compared with other algorithms, the peak signal to noise ratio and structural similarity index of the proposed algorithm are improved by 5.44 dB and 21.08% on average respectively. The average calculation time is only 1.59 s. Based on realizing image compression and accurate reconstruction stably and quickly, the proposed algorithm provides a new method for compressed sensing and image reconstruction.
Available online ,
doi: 10.11999/220934
Abstract:
Millimeter wave Multiple Input and Multiple Output (MIMO) channel exhibits beam sparsity and high directivity in the beam domain, and the beam domain channel pattern is highly correlated with the terminal position. In this paper, the beam domain channel pattern is regarded as a channel fingerprint. A channel fingerprint-based identity spoofing attacks detection scheme is proposed for millimeter-wave MIMO systems. The identity authentication problem is modeled as a binary classification problem of the corresponding channel fingerprint. Then, the supervised learning Support Vector Machine (SVM) algorithm is employed to solve the classification problem. In order to achieve good classification effect, different similarity indexes on channel fingerprint are compared based on the numerical analysis of the beam domain, and the one with the best classification effect is selected as the final classification feature to train the classifier model. The simulation results show that the proposed scheme has good authentication performance even under low signal-to-noise ratio conditions. Compared with the existing relative schemes, the detection accuracy is significantly improved.
Millimeter wave Multiple Input and Multiple Output (MIMO) channel exhibits beam sparsity and high directivity in the beam domain, and the beam domain channel pattern is highly correlated with the terminal position. In this paper, the beam domain channel pattern is regarded as a channel fingerprint. A channel fingerprint-based identity spoofing attacks detection scheme is proposed for millimeter-wave MIMO systems. The identity authentication problem is modeled as a binary classification problem of the corresponding channel fingerprint. Then, the supervised learning Support Vector Machine (SVM) algorithm is employed to solve the classification problem. In order to achieve good classification effect, different similarity indexes on channel fingerprint are compared based on the numerical analysis of the beam domain, and the one with the best classification effect is selected as the final classification feature to train the classifier model. The simulation results show that the proposed scheme has good authentication performance even under low signal-to-noise ratio conditions. Compared with the existing relative schemes, the detection accuracy is significantly improved.
Available online ,
doi: 10.11999/JEIT221084
Abstract:
This paper studies the detection and suppression mechanisms of fly synchronization of Unmanned Aerial Vehicle (UAV) swarm. Fly synchronization process is viewed as emergence in the complex system. A detection algorithm is proposed based on emergence identification with double thresholds. By simultaneously monitoring the entropy difference of flight synchronization process and network connectivity of the target system, the misjudgment of existing algorithms caused by ignoring the network status is overcomed, and the occurrence, achievement, or failure of fly synchronization is accurately identified, which provides a solid prerequisite for the timing control of the suppression mechanism. In-band radio interference behavior is designed under the constraint of average power. The interference behavior modeled from the perspective of degrading the target system’s communication capacity and the effect is analyzed through simulations. It is found that low-intensity continuous interference can effectively delay the fly synchronization process and prolong the time of that. What’s more, it has better concealment. Medium-intensity continuous interference can rapidly stop that process. Based on the above perception, for the first time, countermeasures for the UAV swarm’s fly synchronization are designed according to- different operational intentions of delay and disruption. Simulation results show the effectiveness of the countermeasures.
This paper studies the detection and suppression mechanisms of fly synchronization of Unmanned Aerial Vehicle (UAV) swarm. Fly synchronization process is viewed as emergence in the complex system. A detection algorithm is proposed based on emergence identification with double thresholds. By simultaneously monitoring the entropy difference of flight synchronization process and network connectivity of the target system, the misjudgment of existing algorithms caused by ignoring the network status is overcomed, and the occurrence, achievement, or failure of fly synchronization is accurately identified, which provides a solid prerequisite for the timing control of the suppression mechanism. In-band radio interference behavior is designed under the constraint of average power. The interference behavior modeled from the perspective of degrading the target system’s communication capacity and the effect is analyzed through simulations. It is found that low-intensity continuous interference can effectively delay the fly synchronization process and prolong the time of that. What’s more, it has better concealment. Medium-intensity continuous interference can rapidly stop that process. Based on the above perception, for the first time, countermeasures for the UAV swarm’s fly synchronization are designed according to- different operational intentions of delay and disruption. Simulation results show the effectiveness of the countermeasures.
Available online ,
doi: 10.11999/JEIT221281
Abstract:
A resource allocation scheme to minimize the total power is proposed for IRS-Assisted single cluster uplink Non-Orthogonal Multiple Access (NOMA) systems. Firstly, the optimization problem is constructed to minimize the total power, and the parameters are power for each user and Intelligent Reflecting Surface (IRS) phase shifts. Secondly, the relationship among the power required by single user, the channel, the user's rate requirements and IRS phase shifts is deduced. The joint optimization problem of power and phase shifts is decomposed into several sub-optimization problems with a single parameter. Then, all IRS phase shifts are solved by an iterative method, and the sub-optimization problems with a single parameter are solved in turn during each iteration. Finally, the minimum power required by each user is calculated based on the IRS phase shifts obtained by iteration. Simulation results show that the total power of the proposed scheme is lower than that of existing schemes in the same scenario.
A resource allocation scheme to minimize the total power is proposed for IRS-Assisted single cluster uplink Non-Orthogonal Multiple Access (NOMA) systems. Firstly, the optimization problem is constructed to minimize the total power, and the parameters are power for each user and Intelligent Reflecting Surface (IRS) phase shifts. Secondly, the relationship among the power required by single user, the channel, the user's rate requirements and IRS phase shifts is deduced. The joint optimization problem of power and phase shifts is decomposed into several sub-optimization problems with a single parameter. Then, all IRS phase shifts are solved by an iterative method, and the sub-optimization problems with a single parameter are solved in turn during each iteration. Finally, the minimum power required by each user is calculated based on the IRS phase shifts obtained by iteration. Simulation results show that the total power of the proposed scheme is lower than that of existing schemes in the same scenario.
Available online ,
doi: 10.11999/JEIT221013
Abstract:
Radar-communication integration can realize both target detection and wireless communication, so as to reduce electromagnetic interference and improve spectrum utilization. The integrated signal design of radar and communication is the key to the realization of integrated technology. The common radar communication integration signals based on Orthogonal Frequency Division Multiplexing (OFDM) have the problems of frequency offset sensitivity and excessive out-of-band radiation, so they are not suitable for high-dynamic applications. Considering the advantages of Filter Bank MultiCarrier (FBMC) signal with high Doppler tolerance and low out-of-band leakage, the time-frequency locations of radar and communication subcarriers are optimized under the framework of FBMC, and a design method of FBMC comb spectrum radar-communication integrated signal is proposed. Since there is inherent interference between FBMC signal carriers and symbols, which leads to inaccurate channel estimation and is not suitable for fast time-varying channels, an interleaved comb-shaped auxiliary pilot structure is designed to eliminate inherent interference and achieve channel tracking. In addition, the radar complex signal in the integrated signal introduces real interference to the communication signal. A real interference compensation algorithm is proposed based on interference utilization, which is used to restore the communication signal. The simulation results show that under the fast time-varying channel, the designed radar-communication integrated signal has a lower bit error rate and better radar detection performance in the process of high data rate transmission.
Radar-communication integration can realize both target detection and wireless communication, so as to reduce electromagnetic interference and improve spectrum utilization. The integrated signal design of radar and communication is the key to the realization of integrated technology. The common radar communication integration signals based on Orthogonal Frequency Division Multiplexing (OFDM) have the problems of frequency offset sensitivity and excessive out-of-band radiation, so they are not suitable for high-dynamic applications. Considering the advantages of Filter Bank MultiCarrier (FBMC) signal with high Doppler tolerance and low out-of-band leakage, the time-frequency locations of radar and communication subcarriers are optimized under the framework of FBMC, and a design method of FBMC comb spectrum radar-communication integrated signal is proposed. Since there is inherent interference between FBMC signal carriers and symbols, which leads to inaccurate channel estimation and is not suitable for fast time-varying channels, an interleaved comb-shaped auxiliary pilot structure is designed to eliminate inherent interference and achieve channel tracking. In addition, the radar complex signal in the integrated signal introduces real interference to the communication signal. A real interference compensation algorithm is proposed based on interference utilization, which is used to restore the communication signal. The simulation results show that under the fast time-varying channel, the designed radar-communication integrated signal has a lower bit error rate and better radar detection performance in the process of high data rate transmission.
Available online ,
doi: 10.11999/JEIT221205
Abstract:
Decolorization is an image compression method widely used in various fields, but few researches focus on the mutual conversion technology of color image and grayscale image. In this paper, a deep learning method is used to innovatively propose an invertible decolorization method based on variable augmentation. This method uses variable augmentation technology to ensure that the output has the same number of channels as the input variable, which satisfies the reversible characteristics of the network. Specifically, the proposed method realizes the decolorization through the forward process of the invertible neural network, and realizes the color restoration of grayscale images through the reverse process. The proposed method performs qualitative and quantitative comparisons on VOC2012, NCD, Wallpaper datasets. The experimental results show that the proposed method achieves better results in the evaluation indicators. The quality of the generated images can preserve the characteristics of brightness, color contrast and structural correlation to the greatest extent, both globally and locally.
Decolorization is an image compression method widely used in various fields, but few researches focus on the mutual conversion technology of color image and grayscale image. In this paper, a deep learning method is used to innovatively propose an invertible decolorization method based on variable augmentation. This method uses variable augmentation technology to ensure that the output has the same number of channels as the input variable, which satisfies the reversible characteristics of the network. Specifically, the proposed method realizes the decolorization through the forward process of the invertible neural network, and realizes the color restoration of grayscale images through the reverse process. The proposed method performs qualitative and quantitative comparisons on VOC2012, NCD, Wallpaper datasets. The experimental results show that the proposed method achieves better results in the evaluation indicators. The quality of the generated images can preserve the characteristics of brightness, color contrast and structural correlation to the greatest extent, both globally and locally.
Available online ,
doi: 10.11999/JEIT221289
Abstract:
In this paper, a dual-channel nonlinear feedback architecture is proposed to suppress nonlinear distortion of Power Amplifiers (PA) in the analog domain to improve PA linearity and reduce adjacent channel leakage. In this architecture, a nonlinear extraction loop and a feedback adjustment loop are included to suppress the nonlinearity. First, in the nonlinear extraction loop, the PA input and output signals are extracted by a coupler and aligned with amplitude and phase. Then the two signals are combined to cancel the linear signal and obtain the nonlinear distortion generated by PA. Next, in the feedback adjustment loop, two independent analog channels are used to modify the amplitude and delay of the extracted nonlinear signal before injecting into the PA input port. The delays of these two channels can be finely tuned to ensure the whole feedback structure to behave like a second-order Delta-Sigma modulator, and it shows better distortion suppression performance compared with the single-channel nonlinear feedback architecture. By configuring the feedback channel parameters through the proposed method, flexible suppression of nonlinear distortion at different target frequency ranges can be achieved. An experimental platform using a commercial PA chip CMPA0060002F is designed for verification. For a test signal with a bandwidth of 40 MHz and a carrier frequency of 780 MHz, under the current hardware feedback delay of 6ns, the Adjacent Channel Leakage Ratio (ACLR) single sideband can be improved by 11 dB or double sideband is improved by 6 dB, with a total feedback delay of 6 ns. Better performance can be expected by integrating this method into the PA designing stage with a reduced feedback delay.
In this paper, a dual-channel nonlinear feedback architecture is proposed to suppress nonlinear distortion of Power Amplifiers (PA) in the analog domain to improve PA linearity and reduce adjacent channel leakage. In this architecture, a nonlinear extraction loop and a feedback adjustment loop are included to suppress the nonlinearity. First, in the nonlinear extraction loop, the PA input and output signals are extracted by a coupler and aligned with amplitude and phase. Then the two signals are combined to cancel the linear signal and obtain the nonlinear distortion generated by PA. Next, in the feedback adjustment loop, two independent analog channels are used to modify the amplitude and delay of the extracted nonlinear signal before injecting into the PA input port. The delays of these two channels can be finely tuned to ensure the whole feedback structure to behave like a second-order Delta-Sigma modulator, and it shows better distortion suppression performance compared with the single-channel nonlinear feedback architecture. By configuring the feedback channel parameters through the proposed method, flexible suppression of nonlinear distortion at different target frequency ranges can be achieved. An experimental platform using a commercial PA chip CMPA0060002F is designed for verification. For a test signal with a bandwidth of 40 MHz and a carrier frequency of 780 MHz, under the current hardware feedback delay of 6ns, the Adjacent Channel Leakage Ratio (ACLR) single sideband can be improved by 11 dB or double sideband is improved by 6 dB, with a total feedback delay of 6 ns. Better performance can be expected by integrating this method into the PA designing stage with a reduced feedback delay.
Available online ,
doi: 10.11999/JEIT221292
Abstract:
Eight-Sided Fortress(ESF), an improved lightweight block cipher based on LBlock, has excellent software and hardware implementation efficiency. For the security of ESF, with the help of automated search tools, the algorithm is evaluated for security using the impossible differential cryptanalysis. Firstly, an impossible differential search model based on Mixed Integer Linear Programming (MILP) is built by combining the structure of ESF algorithm and the differential propagation of\begin{document}$ S $\end{document} \begin{document}$ S $\end{document} \begin{document}$ {2^{60.16}} $\end{document} \begin{document}$ {2^{67.44}} $\end{document}
Eight-Sided Fortress(ESF), an improved lightweight block cipher based on LBlock, has excellent software and hardware implementation efficiency. For the security of ESF, with the help of automated search tools, the algorithm is evaluated for security using the impossible differential cryptanalysis. Firstly, an impossible differential search model based on Mixed Integer Linear Programming (MILP) is built by combining the structure of ESF algorithm and the differential propagation of
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Multi-User and Multi-Target Constant Waveform Design of Dual-Function Radar and Communication System
2023, 45(11): 3821-3829.
doi: 10.11999/JEIT230827
Abstract:
The Dual-Functional Radar-Communication (DFRC) system can effectively utilize hardware and spectrum resources, which is an effective way to solve the shortage of the wireless spectrum resource. In this paper, for the scenario of simultaneous multi-target detection and multi-user communication, the Signal-to-Interference-Noise Ratio (SINR) of the radar received echo is used as an index to guarantee the detection performance, and the Multi-User Interference (MUI) of the communication is used as a communication index to guarantee the transmission performance of communication. Meanwhile, constraints on the constant modulus of the waveform are added to ensure that the power amplifier at the transmitter operates in the saturation region. The paper proposes a mathematical model for waveform design that maximizes the minimum SINR of the radar multi-target echoes while satisfying a certain amount of the communication MUI energy by jointly optimizing the waveforms as well as the filters. For this optimization problem, the method of alternating iterative optimization is adopted to solve the problem. Simulation results show that the designed waveform ensures both radar and communication related performance in simultaneous multi-target detection and multi-user communication scenarios.
The Dual-Functional Radar-Communication (DFRC) system can effectively utilize hardware and spectrum resources, which is an effective way to solve the shortage of the wireless spectrum resource. In this paper, for the scenario of simultaneous multi-target detection and multi-user communication, the Signal-to-Interference-Noise Ratio (SINR) of the radar received echo is used as an index to guarantee the detection performance, and the Multi-User Interference (MUI) of the communication is used as a communication index to guarantee the transmission performance of communication. Meanwhile, constraints on the constant modulus of the waveform are added to ensure that the power amplifier at the transmitter operates in the saturation region. The paper proposes a mathematical model for waveform design that maximizes the minimum SINR of the radar multi-target echoes while satisfying a certain amount of the communication MUI energy by jointly optimizing the waveforms as well as the filters. For this optimization problem, the method of alternating iterative optimization is adopted to solve the problem. Simulation results show that the designed waveform ensures both radar and communication related performance in simultaneous multi-target detection and multi-user communication scenarios.
2023, 45(11): 3830-3838.
doi: 10.11999/JEIT230787
Abstract:
As an increasing number of high-frequency circuits are integrated into chips, high-frequency Integrated Circuit ElectroMagnetic Compatibility (IC-EMC) problem of chips is becoming increasingly prominent. The IC-Stripline cell is an important device for measuring radiated emission and immunity of integrated chips. However, bandwidth is the major factor limiting its application. According to IEC standard, the paper applies magnetic absorbing materials to the IC-Stripline cell to expand the working bandwidth of the cell, and proposes a method combining Particle Swarm Optimization (PSO) and Dichotomy to calculate the available electromagnetic parameter range of the magnetic absorbing material. Experimental results indicate that the material can improve the operational bandwidth of the IC-Stripline cell from 0～6 GHz to a maximum of 0～10 GHz. The electromagnetic parameters of the selected magnetic absorbing material are consistent with the calculations over the range of 0～9 GHz, while the parameters exceed the calculation results for frequencies >9 GHz. The S parameter measurements of the IC-Stripline cell using this material reveal that the material indeed improves the operational bandwidth from 0～6 GHz to 0～9 GHz, which is consistent with the calculations results and validates the effectiveness of the electromagnetic parameter range determination method. Compared to traditional methods, the efficiency of this method is increased by 73.3%. Furthermore, the proposed method is applicable to parameter range calculation problems under similar objective constraints.
As an increasing number of high-frequency circuits are integrated into chips, high-frequency Integrated Circuit ElectroMagnetic Compatibility (IC-EMC) problem of chips is becoming increasingly prominent. The IC-Stripline cell is an important device for measuring radiated emission and immunity of integrated chips. However, bandwidth is the major factor limiting its application. According to IEC standard, the paper applies magnetic absorbing materials to the IC-Stripline cell to expand the working bandwidth of the cell, and proposes a method combining Particle Swarm Optimization (PSO) and Dichotomy to calculate the available electromagnetic parameter range of the magnetic absorbing material. Experimental results indicate that the material can improve the operational bandwidth of the IC-Stripline cell from 0～6 GHz to a maximum of 0～10 GHz. The electromagnetic parameters of the selected magnetic absorbing material are consistent with the calculations over the range of 0～9 GHz, while the parameters exceed the calculation results for frequencies >9 GHz. The S parameter measurements of the IC-Stripline cell using this material reveal that the material indeed improves the operational bandwidth from 0～6 GHz to 0～9 GHz, which is consistent with the calculations results and validates the effectiveness of the electromagnetic parameter range determination method. Compared to traditional methods, the efficiency of this method is increased by 73.3%. Furthermore, the proposed method is applicable to parameter range calculation problems under similar objective constraints.
2023, 45(11): 3839-3847.
doi: 10.11999/JEIT221216
Abstract:
An adaptive Rao detection method for radar targets is proposed based on the priori knowledge of sea clutter to improve the radar’s target detection performance in non-Gaussian and nonhomogeneous sea clutter. First, the texture component and the speckle covariance matrix of sea clutter are modeled as an inverse Gaussian random variable and an inverse complex Wishart random matrix, respectively. Then, an adaptive Rao detection method for radar targets, with quite similar characteristics as sea clutter, is designed based on the Rao test and unknown parameter estimation. The detection method is verified by theoretical derivation and experiments in demonstrating constant false alarm characteristics for the mean power and covariance mean matrix of sea clutter. The experimental results of the simulated and experimental data reveal that the proposed detection method outperforms existing detection methods in non-Gaussian and nonhomogeneous sea clutter environments with good robustness.
An adaptive Rao detection method for radar targets is proposed based on the priori knowledge of sea clutter to improve the radar’s target detection performance in non-Gaussian and nonhomogeneous sea clutter. First, the texture component and the speckle covariance matrix of sea clutter are modeled as an inverse Gaussian random variable and an inverse complex Wishart random matrix, respectively. Then, an adaptive Rao detection method for radar targets, with quite similar characteristics as sea clutter, is designed based on the Rao test and unknown parameter estimation. The detection method is verified by theoretical derivation and experiments in demonstrating constant false alarm characteristics for the mean power and covariance mean matrix of sea clutter. The experimental results of the simulated and experimental data reveal that the proposed detection method outperforms existing detection methods in non-Gaussian and nonhomogeneous sea clutter environments with good robustness.
2023, 45(11): 3848-3859.
doi: 10.11999/JEIT230767
Abstract:
This study addresses the joint design problem of radar transmit waveform, receive filter and Reconfigurable Intelligent Surface (RIS) reflecting coefficients with an aim to enhance the target detection performance of a RIS-aided radar system. With restrictions on the finite phases of the radar waveform and RIS reflecting coefficients, the performance enhancement problem is formulated as a nonconvex joint design, in which the system Signal-to-Interference-plus-Noise-Ratio (SINR) is taken as the optimization objective. A novel cyclic optimization algorithm is developed to tackle this. In each cycle, two subproblems with respect to waveform and RIS reflecting coefficients are involved and are resolved by leveraging the Minorization Maximization (MM) strategy. The simulation results highlight the effectiveness of the proposed algorithm for providing high-quality RIS reflecting coefficients, radar transmit waveform, and receive filter.
This study addresses the joint design problem of radar transmit waveform, receive filter and Reconfigurable Intelligent Surface (RIS) reflecting coefficients with an aim to enhance the target detection performance of a RIS-aided radar system. With restrictions on the finite phases of the radar waveform and RIS reflecting coefficients, the performance enhancement problem is formulated as a nonconvex joint design, in which the system Signal-to-Interference-plus-Noise-Ratio (SINR) is taken as the optimization objective. A novel cyclic optimization algorithm is developed to tackle this. In each cycle, two subproblems with respect to waveform and RIS reflecting coefficients are involved and are resolved by leveraging the Minorization Maximization (MM) strategy. The simulation results highlight the effectiveness of the proposed algorithm for providing high-quality RIS reflecting coefficients, radar transmit waveform, and receive filter.
2023, 45(11): 3860-3867.
doi: 10.11999/JEIT221259
Abstract:
This paper employs the difference coarray structures of transmit/receive EMVS to enhance the multidimensional parameter estimation performance in bistatic EMVS-MIMO radar. The difference coarrays of transmit/receive EMVS are built through the high-order tensor operation for receiving data. First, a fifth-order tensor model with the difference coarray of the original transmits/receive EMVS can be obtained by applying the tensor permutation rule and generalized tensorization. Additionally, the repeated elements in the difference coarray can be removed by using two selection matrices, where the obtained degree of freedom of the difference coarray is twice that of the original array. Then, a third-order tensor model with the third way fixed at 36 can be developed by using the generalized tensorization again. Finally, the PARAFAC algorithm is adopted to effectively estimate the transmit/receive four-dimensional parameter. Simulation demonstrate that the difference coarray can efficiently enhance the multi-dimensional parameter estimation performance in bistatic EMVS-MIMO radar.
This paper employs the difference coarray structures of transmit/receive EMVS to enhance the multidimensional parameter estimation performance in bistatic EMVS-MIMO radar. The difference coarrays of transmit/receive EMVS are built through the high-order tensor operation for receiving data. First, a fifth-order tensor model with the difference coarray of the original transmits/receive EMVS can be obtained by applying the tensor permutation rule and generalized tensorization. Additionally, the repeated elements in the difference coarray can be removed by using two selection matrices, where the obtained degree of freedom of the difference coarray is twice that of the original array. Then, a third-order tensor model with the third way fixed at 36 can be developed by using the generalized tensorization again. Finally, the PARAFAC algorithm is adopted to effectively estimate the transmit/receive four-dimensional parameter. Simulation demonstrate that the difference coarray can efficiently enhance the multi-dimensional parameter estimation performance in bistatic EMVS-MIMO radar.
2023, 45(11): 3868-3876.
doi: 10.11999/JEIT221362
Abstract:
The deficiencies in the commonly used passive localization technologies using multiple observers are the failure of the emitter with a very low sidelobe based on the Time Difference of Arrival (TDOA)/ Frequency Difference of Arrival (FDOA) and the high cost and system complexity based on the Direction of Arrival (DOA), a novel passive localization system based on the Phase Difference of Arrival (PDOA) is presented. Herein, a Long Baseline Interferometer (LBI) comprising at least two sets of the receiving antenna and channel on each observer is used to measure the PDOA and locate the emitter. Moreover,to solve the nonlinearity and discontinuity caused by the 2π ambiguity, an iterative optimization method based on multiple hypotheses is proposed. First, a pair of PDOA is selected to obtain multiple initial values; Second, the Gauss-Newton (GN) method is applied to update each initial value; Finally, the cost function corresponding to the updated estimate is calculated. The result with the minimum cost function is selected as the final estimate. The initial values of the emitter position can be robustly obtained with moderate computational complexity. Simulation results show that the Root Mean Square Error (RMSE) of the proposed method can reach the Cramer-Rao Lower Bound (CRLB) at moderate Gaussian measurement noise.
The deficiencies in the commonly used passive localization technologies using multiple observers are the failure of the emitter with a very low sidelobe based on the Time Difference of Arrival (TDOA)/ Frequency Difference of Arrival (FDOA) and the high cost and system complexity based on the Direction of Arrival (DOA), a novel passive localization system based on the Phase Difference of Arrival (PDOA) is presented. Herein, a Long Baseline Interferometer (LBI) comprising at least two sets of the receiving antenna and channel on each observer is used to measure the PDOA and locate the emitter. Moreover,to solve the nonlinearity and discontinuity caused by the 2π ambiguity, an iterative optimization method based on multiple hypotheses is proposed. First, a pair of PDOA is selected to obtain multiple initial values; Second, the Gauss-Newton (GN) method is applied to update each initial value; Finally, the cost function corresponding to the updated estimate is calculated. The result with the minimum cost function is selected as the final estimate. The initial values of the emitter position can be robustly obtained with moderate computational complexity. Simulation results show that the Root Mean Square Error (RMSE) of the proposed method can reach the Cramer-Rao Lower Bound (CRLB) at moderate Gaussian measurement noise.
2023, 45(11): 3877-3886.
doi: 10.11999/JEIT221469
Abstract:
Interrupted Sampling Repeater Jamming (ISRJ) has attracted increasing attention as a new type of active jamming. Polarization is an important parameter for characterizing an electromagnetic wave vector and can substantially improve radar anti-jamming performance. Therefore, in this study, the anti-ISRJ method of polarimetric radar is studied. Here, better anti-jamming performance than that of traditional radar is obtained through waveform design and optimization. Additionally, because the modulation effect of target characteristics on a signal is neglected in the existing characterization of the anti-ISRJ problem under wideband radar conditions, this paper includes target characteristics factors to the mathematical expression of SJR. Finally, on this basis, a waveform design method of anti-ISRJ polarimetric radar with Doppler tolerance is proposed. Experiments using the measured target data show that compared with traditional radar, the introduction of polarization information improves substantially radar ISRJ suppression performance; moreover, under wideband conditions, the modulation effect of the extended target on the signal must be considered when calculating SJR.
Interrupted Sampling Repeater Jamming (ISRJ) has attracted increasing attention as a new type of active jamming. Polarization is an important parameter for characterizing an electromagnetic wave vector and can substantially improve radar anti-jamming performance. Therefore, in this study, the anti-ISRJ method of polarimetric radar is studied. Here, better anti-jamming performance than that of traditional radar is obtained through waveform design and optimization. Additionally, because the modulation effect of target characteristics on a signal is neglected in the existing characterization of the anti-ISRJ problem under wideband radar conditions, this paper includes target characteristics factors to the mathematical expression of SJR. Finally, on this basis, a waveform design method of anti-ISRJ polarimetric radar with Doppler tolerance is proposed. Experiments using the measured target data show that compared with traditional radar, the introduction of polarization information improves substantially radar ISRJ suppression performance; moreover, under wideband conditions, the modulation effect of the extended target on the signal must be considered when calculating SJR.
2023, 45(11): 3896-3905.
doi: 10.11999/JEIT230331
Abstract:
Interrupted Sampling Repeater Jamming (ISRJ) is an advanced active coherent jamming technology, which has great influence on the detection performance of radar, and the existing anti-ISRJ methods need to solve complex waveform optimization problems and interference recognition and elimination. Therefore, on the basis of in-depth study of ISRJ, an anti-ISRJ method based on complete complementary codes is proposed. Considering the characteristics of ISRJ sampling discontinuity in time domain, all complementary waveforms in the complete complementary code are integrated into a single pulse radar waveform through sub-pulse cover using the method of orthogonal in the frequency domain. Then, based on the intra-pulse segmental pulse compression processing method, utilizing the ideal cross-correlation and autocorrelation characteristics of the complete complementary code waveform, the mismatched filter coefficients are designed to suppress ISRJ and obtain lower range sidelobes. Compared to existing anti-ISRJ methods, the proposed method has stronger online design capability and obviates the need for interference recognition and elimination. The simulation results demonstrate that the various ISRJs can be effectively suppressed by the designed waveform and has high Doppler tolerance.
Interrupted Sampling Repeater Jamming (ISRJ) is an advanced active coherent jamming technology, which has great influence on the detection performance of radar, and the existing anti-ISRJ methods need to solve complex waveform optimization problems and interference recognition and elimination. Therefore, on the basis of in-depth study of ISRJ, an anti-ISRJ method based on complete complementary codes is proposed. Considering the characteristics of ISRJ sampling discontinuity in time domain, all complementary waveforms in the complete complementary code are integrated into a single pulse radar waveform through sub-pulse cover using the method of orthogonal in the frequency domain. Then, based on the intra-pulse segmental pulse compression processing method, utilizing the ideal cross-correlation and autocorrelation characteristics of the complete complementary code waveform, the mismatched filter coefficients are designed to suppress ISRJ and obtain lower range sidelobes. Compared to existing anti-ISRJ methods, the proposed method has stronger online design capability and obviates the need for interference recognition and elimination. The simulation results demonstrate that the various ISRJs can be effectively suppressed by the designed waveform and has high Doppler tolerance.
2023, 45(11): 3906-3917.
doi: 10.11999/JEIT230740
Abstract:
Interrupted-Sampling Repeater Jamming (ISRJ) is an advanced radar interference, which is based on the under-sampling theory. The kind of this interference may introduce a train of false targets into the High-Resolution Range Profile (HRRP), and create some challenges for the target detection. To solve this dilemma, a multi-subband matching filter method is proposed. Firstly, the subband matching filters is obtained by the traditional matching filter. Then, the signal models of the subband matching filters are established by the difference between the ISRJ and the target echo. As the ISRJ is sensitive to the time width of the subband matching filter, a multi-subband matching filter method is presented for the target detection in ISRJ back-ground. Simulation results indicate that the ISRJ can be suppressed by the multi-subband matching filter without the prior information about the ISRJ, and the detection probability of the radar target can be above 80% when the signal to interference ratio of the radar is above –20 dB.
Interrupted-Sampling Repeater Jamming (ISRJ) is an advanced radar interference, which is based on the under-sampling theory. The kind of this interference may introduce a train of false targets into the High-Resolution Range Profile (HRRP), and create some challenges for the target detection. To solve this dilemma, a multi-subband matching filter method is proposed. Firstly, the subband matching filters is obtained by the traditional matching filter. Then, the signal models of the subband matching filters are established by the difference between the ISRJ and the target echo. As the ISRJ is sensitive to the time width of the subband matching filter, a multi-subband matching filter method is presented for the target detection in ISRJ back-ground. Simulation results indicate that the ISRJ can be suppressed by the multi-subband matching filter without the prior information about the ISRJ, and the detection probability of the radar target can be above 80% when the signal to interference ratio of the radar is above –20 dB.
2023, 45(11): 3918-3926.
doi: 10.11999/JEIT220969
Abstract:
Multi-Function Radio Frequency (MFRF) systems based on Multiple-Input-Multiple-Output (MIMO) array can synthesize different signals that can realize multiple functions at different angles via waveform optimization. However, due to the angle uncertainties, the waveforms synthesized by MFRF systems might be distorted and the performance of the systems might degrade as well. The robust waveform design algorithm for MFRF systems under angle uncertainties is studied in this paper. Firstly, a waveform optimization based on Min-Max framework is proposed. Additionally, the Peak-to-Average-Power-Ratio (PAPR) constraint is enforced to reduce the waveform distortion caused by nonlinearity of the power amplifiers. To tackle this problem, an algorithm based on the Alternating Direction Method of Multipliers (ADMM) and Majorization-Minimization (MM) algorithm is derived. Simulation results show that the proposed algorithm can produce signals with different functions in different regions even with angle uncertainties.
Multi-Function Radio Frequency (MFRF) systems based on Multiple-Input-Multiple-Output (MIMO) array can synthesize different signals that can realize multiple functions at different angles via waveform optimization. However, due to the angle uncertainties, the waveforms synthesized by MFRF systems might be distorted and the performance of the systems might degrade as well. The robust waveform design algorithm for MFRF systems under angle uncertainties is studied in this paper. Firstly, a waveform optimization based on Min-Max framework is proposed. Additionally, the Peak-to-Average-Power-Ratio (PAPR) constraint is enforced to reduce the waveform distortion caused by nonlinearity of the power amplifiers. To tackle this problem, an algorithm based on the Alternating Direction Method of Multipliers (ADMM) and Majorization-Minimization (MM) algorithm is derived. Simulation results show that the proposed algorithm can produce signals with different functions in different regions even with angle uncertainties.
2023, 45(11): 3927-3934.
doi: 10.11999/JEIT230415
Abstract:
A fast power spectrum fitting method based on Orthogonal Basis Searching (OBS) is proposed to meet the requirements of Gaussian pulse combination waveform design for Carrier free Ultra Wide-Band (UWB) fuze. Multiple candidate Gaussian pulse functions are constructed according to the value range of the pulse forming factor, and on the basis of power spectrum design by maximizing mutual information, power spectrum fitting is carried out in a cyclic iteration method. In each iteration, Schmidt Orthogonalization is performed on the candidate Gaussian pulse functions, and the best one matches the residual amplitude spectrum is quickly found through the inner product calculation. Finally, the weighting coefficient is determined according to the matrix relationship between the selected Gaussian pulse functions and their Orthogonalization functions, so as to obtain the waveform combined with multi-pulse, which makes the fitted power spectrum and the designed one achieve good similarity. The effectiveness of the proposed method and its efficiency compared to the particle swarm optimization algorithm have been verified through simulation.
A fast power spectrum fitting method based on Orthogonal Basis Searching (OBS) is proposed to meet the requirements of Gaussian pulse combination waveform design for Carrier free Ultra Wide-Band (UWB) fuze. Multiple candidate Gaussian pulse functions are constructed according to the value range of the pulse forming factor, and on the basis of power spectrum design by maximizing mutual information, power spectrum fitting is carried out in a cyclic iteration method. In each iteration, Schmidt Orthogonalization is performed on the candidate Gaussian pulse functions, and the best one matches the residual amplitude spectrum is quickly found through the inner product calculation. Finally, the weighting coefficient is determined according to the matrix relationship between the selected Gaussian pulse functions and their Orthogonalization functions, so as to obtain the waveform combined with multi-pulse, which makes the fitted power spectrum and the designed one achieve good similarity. The effectiveness of the proposed method and its efficiency compared to the particle swarm optimization algorithm have been verified through simulation.
2023, 45(11): 3935-3944.
doi: 10.11999/JEIT230914
Abstract:
The demand for real-time communication of underwater information is rising by the day. Traditional communication technologies, such as underwater acoustic communication and optical communication, have inherent drawbacks in terms of transmission security and stability, and it is difficult to build a transmission rate breakthrough. As a result, it is critical to investigate new technologies. To address this issue, some researchers have proposed a miniaturized antenna with new mechanisms, materials, and technology, which is expected to realize a leap in size and performance of low-frequency antennas and transform underwater communication technology. This type of acoustically excited miniaturized antenna is studied in this paper. First, the radiation mechanism and theoretical model of the antenna are explained and established, and the effect of various material factors on the antenna's performance is investigated. The model parameters are then used to develop and manufacture a piezoelectric acoustically excited antenna prototype based on lithium niobate (LiNbO3) crystal. The experimental findings reveal that at the resonance frequency of 40.83 kHz, the peak receiving voltage is 22 times that of the monopole antenna, and the radiation efficiency is more than 400 times that of the latter. Finally, the antenna's pattern test and radiation efficiency calculation are performed. The results suggest that acoustically excited antenna technology based on piezoelectric crystals has a lot of potential for low-frequency miniaturized and motorized underwater wireless communication equipment.
The demand for real-time communication of underwater information is rising by the day. Traditional communication technologies, such as underwater acoustic communication and optical communication, have inherent drawbacks in terms of transmission security and stability, and it is difficult to build a transmission rate breakthrough. As a result, it is critical to investigate new technologies. To address this issue, some researchers have proposed a miniaturized antenna with new mechanisms, materials, and technology, which is expected to realize a leap in size and performance of low-frequency antennas and transform underwater communication technology. This type of acoustically excited miniaturized antenna is studied in this paper. First, the radiation mechanism and theoretical model of the antenna are explained and established, and the effect of various material factors on the antenna's performance is investigated. The model parameters are then used to develop and manufacture a piezoelectric acoustically excited antenna prototype based on lithium niobate (LiNbO3) crystal. The experimental findings reveal that at the resonance frequency of 40.83 kHz, the peak receiving voltage is 22 times that of the monopole antenna, and the radiation efficiency is more than 400 times that of the latter. Finally, the antenna's pattern test and radiation efficiency calculation are performed. The results suggest that acoustically excited antenna technology based on piezoelectric crystals has a lot of potential for low-frequency miniaturized and motorized underwater wireless communication equipment.
2023, 45(11): 3945-3954.
doi: 10.11999/JEIT230762
Abstract:
In order to analyze the coupling effect between periodic structures such as Energy Selection Structures (ESS) and antennas when ESS are used as radomes, and improve analysis efficiency, an analysis method based on Poynting vector methods is proposed in this paper. In the perspective of reciprocity between transmission and reception, the electromagnetic characteristics of antennas are analyzed as transmitters rather than receivers in conventional methods. From the perspective of reception, an antenna is regarded as a device that captures energy from free space. Therefore, the energy distribution can be described by the Poynting energy flow density curve. Similarly, the disturbance of electromagnetic waves caused by ESS can also be described by Poynting streamlines. Therefore, antennas, protective structures, and their coupling effects can be studied and analyzed through Poynting streamlines. The results indicate that the proposed method poses a good consistency with conventional analysis methods. Compared to conventional analysis methods, the proposed method in this paper can simultaneously visualize and quantitatively evaluate the coupling effect between antennas and ESS. The results can be used for the design of the size, shape, and optimal installation position of ESS, thus significantly improving design efficiency.
In order to analyze the coupling effect between periodic structures such as Energy Selection Structures (ESS) and antennas when ESS are used as radomes, and improve analysis efficiency, an analysis method based on Poynting vector methods is proposed in this paper. In the perspective of reciprocity between transmission and reception, the electromagnetic characteristics of antennas are analyzed as transmitters rather than receivers in conventional methods. From the perspective of reception, an antenna is regarded as a device that captures energy from free space. Therefore, the energy distribution can be described by the Poynting energy flow density curve. Similarly, the disturbance of electromagnetic waves caused by ESS can also be described by Poynting streamlines. Therefore, antennas, protective structures, and their coupling effects can be studied and analyzed through Poynting streamlines. The results indicate that the proposed method poses a good consistency with conventional analysis methods. Compared to conventional analysis methods, the proposed method in this paper can simultaneously visualize and quantitatively evaluate the coupling effect between antennas and ESS. The results can be used for the design of the size, shape, and optimal installation position of ESS, thus significantly improving design efficiency.
2023, 45(11): 3955-3964.
doi: 10.11999/JEIT230805
Abstract:
As the secure core of chips and systems, Physical Unclonable Function(PUF) is widely applied to key management, device authentication, and fingerprint identification fields. Among all the existing security solutions, PUF is one of the most effective methods to solve the information security problems of chips and systems. Combined with the characteristics of PUF and FPGA, a Configurable Butterfly Strong PUF (CBS-PUF) based on a delay chain is proposed in this paper. An asymmetric delay chain is constructed by using three basic elements of FPGA and a reconfigurable butterfly strong PUF is established with the cross-couped symmetric delay chain. Further, an FPGA-based PUF test platform is built and a response acquisition tool is designed to acquire the PUF challenge-response pair. Finally, the reliability, uniformity, and randomness of CBS-PUF are analyzed, and the anti-modeling attack scheme is given. The experimental results show that the randomness, reliability, and uniqueness of the proposed PUF are close to the ideal value (51.02%, 98.38%, and 47.2% respectively), and the proposed PUF presents an appealing option for the security fields of chips and systems.
As the secure core of chips and systems, Physical Unclonable Function(PUF) is widely applied to key management, device authentication, and fingerprint identification fields. Among all the existing security solutions, PUF is one of the most effective methods to solve the information security problems of chips and systems. Combined with the characteristics of PUF and FPGA, a Configurable Butterfly Strong PUF (CBS-PUF) based on a delay chain is proposed in this paper. An asymmetric delay chain is constructed by using three basic elements of FPGA and a reconfigurable butterfly strong PUF is established with the cross-couped symmetric delay chain. Further, an FPGA-based PUF test platform is built and a response acquisition tool is designed to acquire the PUF challenge-response pair. Finally, the reliability, uniformity, and randomness of CBS-PUF are analyzed, and the anti-modeling attack scheme is given. The experimental results show that the randomness, reliability, and uniqueness of the proposed PUF are close to the ideal value (51.02%, 98.38%, and 47.2% respectively), and the proposed PUF presents an appealing option for the security fields of chips and systems.
2023, 45(11): 3965-3972.
doi: 10.11999/JEIT230438
Abstract:
As the feature size of integrated circuits scales down, the problem of the Single Event Transients (SET) in CMOS integrated circuits is becoming more and more serious. In order to improve the hardening effect of the Low-DropOut regulators (LDO), the mechanism of the SET in a LDO fabricated on 28 nm CMOS technology is studied by SPICE circuit simulation and heavy ion experiment. The influence of the size of the key components on the SET in LDO is also studied. The hardening methods for LDO is proposed. The SPICE circuit simulation results show that the most sensitive nodes are located in the Error Amplifier (EA). The equivalent capacitance on the gate node of the power MOSFET can significantly influence the amplitude of the single event transients and slightly influence the width. The size of the relevant devices in the error amplifier can influence both amplitude and width of the SETs. The LDO is hardened by adding the capacitance on the gate node of power MOSFET and adjusting the size of the relevant devices in the error amplifier. The results of the simulation and the experiment show that the hardening method can significantly decrease the amplitude and width of the SETs.
As the feature size of integrated circuits scales down, the problem of the Single Event Transients (SET) in CMOS integrated circuits is becoming more and more serious. In order to improve the hardening effect of the Low-DropOut regulators (LDO), the mechanism of the SET in a LDO fabricated on 28 nm CMOS technology is studied by SPICE circuit simulation and heavy ion experiment. The influence of the size of the key components on the SET in LDO is also studied. The hardening methods for LDO is proposed. The SPICE circuit simulation results show that the most sensitive nodes are located in the Error Amplifier (EA). The equivalent capacitance on the gate node of the power MOSFET can significantly influence the amplitude of the single event transients and slightly influence the width. The size of the relevant devices in the error amplifier can influence both amplitude and width of the SETs. The LDO is hardened by adding the capacitance on the gate node of power MOSFET and adjusting the size of the relevant devices in the error amplifier. The results of the simulation and the experiment show that the hardening method can significantly decrease the amplitude and width of the SETs.
2023, 45(11): 3973-3983.
doi: 10.11999/JEIT230562
Abstract:
In this paper, one design method of decoupling wideband antenna array based on multi-route decoupling network is proposed. At the beginning, the decoupling and matching conditions of the common multi-route decoupling network model are derived by employing node analysis, and the general design process is obtained. Then, the proposed decoupling network is applied to a two-element antipodal Vivaldi array, and its dimensional parameters are achieved via the designing basis at low band and the design process. Also, gradient transmission lines are added to extend the decoupling bandwidth. The measured results indicate that the isolation is higher than 20 dB in the operation band of 3.34～13 GHz (3.89:1), which is 58.8% wider than that of the coupled array. Finally, the decoupling effectiveness is further verified in one-dimensional eight-element array, and in-band isolation is always higher than 20 dB. Moreover, the array owns good radiation performance in the scanning range of ±60°. The presented multi-route decoupling network features generality, simple structure and wideband decoupling performance, and is potential in the application of phased arrays and large-scale communication systems.
In this paper, one design method of decoupling wideband antenna array based on multi-route decoupling network is proposed. At the beginning, the decoupling and matching conditions of the common multi-route decoupling network model are derived by employing node analysis, and the general design process is obtained. Then, the proposed decoupling network is applied to a two-element antipodal Vivaldi array, and its dimensional parameters are achieved via the designing basis at low band and the design process. Also, gradient transmission lines are added to extend the decoupling bandwidth. The measured results indicate that the isolation is higher than 20 dB in the operation band of 3.34～13 GHz (3.89:1), which is 58.8% wider than that of the coupled array. Finally, the decoupling effectiveness is further verified in one-dimensional eight-element array, and in-band isolation is always higher than 20 dB. Moreover, the array owns good radiation performance in the scanning range of ±60°. The presented multi-route decoupling network features generality, simple structure and wideband decoupling performance, and is potential in the application of phased arrays and large-scale communication systems.
2023, 45(11): 3984-3990.
doi: 10.11999/JEIT230668
Abstract:
A 16 Gbit/s Serializer/Deserializer interface(SerDes) chip which is composed of 4 lanes and 2 Phase-Locked Loop(PLLs), is designed in bulk CMOS technology. A negative impedance structure Continuous Time Linear Equalizer(CTLE) is used in the Analog Front End(AFE) of the receiver to obtain 22.9 dB high frequency gain. Further, 5-tap Decision Feedback Equalizer(DFE) is used to compensate the Inter Symbol Interference(ISI), and tap1 unrolled to obtain sufficient timing constraints. Least Mean Square(LMS) algorithm is used to control adaptive CTLE and DFE compensation coefficient to counter the influence of process, power supply and temperature fluctuations. The measurement results show that, the total power consumption is 615mW when working at 16 Gbit/s. Transmitter output signal eye height is 143 mV, width is 43.8 ps(0.7UI), jitter tolerance of the receiver contents the PCIe4.0 protocol requirements at all frequency, working temperature cover –55°C～125°C, power supply voltage cover 0.9 V±10%, bit error rate is less than 1E-12.
A 16 Gbit/s Serializer/Deserializer interface(SerDes) chip which is composed of 4 lanes and 2 Phase-Locked Loop(PLLs), is designed in bulk CMOS technology. A negative impedance structure Continuous Time Linear Equalizer(CTLE) is used in the Analog Front End(AFE) of the receiver to obtain 22.9 dB high frequency gain. Further, 5-tap Decision Feedback Equalizer(DFE) is used to compensate the Inter Symbol Interference(ISI), and tap1 unrolled to obtain sufficient timing constraints. Least Mean Square(LMS) algorithm is used to control adaptive CTLE and DFE compensation coefficient to counter the influence of process, power supply and temperature fluctuations. The measurement results show that, the total power consumption is 615mW when working at 16 Gbit/s. Transmitter output signal eye height is 143 mV, width is 43.8 ps(0.7UI), jitter tolerance of the receiver contents the PCIe4.0 protocol requirements at all frequency, working temperature cover –55°C～125°C, power supply voltage cover 0.9 V±10%, bit error rate is less than 1E-12.
2023, 45(11): 3991-4002.
doi: 10.11999/JEIT230593
Abstract:
In order to cope with broadband blocking interference, the integrated communication and interference cancellation system usually applies the interference cancellation technology based on subband division to improve the broadband interference suppression capability. To guarantee the communication performance meanwhile, it is required to reconstruct the subband signal to communication signal. In this paper, the combination of analog circuits and digital processing is used to build a subband division and signal reconstruction framework. The wide filtering in the first-stage is realized through analog filters to reduce the signal processing bandwidth. The narrow filtering in the second-stage is completed by digital filters to improve further the signal-to-noise ratio. This paper focusses on the problem of cross-subband reconstruction distortion in the communication signals’ subband division process. The time-frequency domain model of the subband division and signal reconstruction system is established to analyze the influence of the amplitude and phase inconsistency between subbands. To solve the inconsistency problem, the phase calibration method and the filter amplitude-frequency optimization method are proposed. The methods are to ensure the approximately distortion-free reconstruction of the cross-subband signal. Simulation and experiment results show that the amplitude-frequency response of the filter designed in the paper has good reconstruction accuracy. The phase calibration method solves the phase distortion problem of cross-subband signal reconstruction, and reduces effectively the bit error rate of reconstructed communication signals.
In order to cope with broadband blocking interference, the integrated communication and interference cancellation system usually applies the interference cancellation technology based on subband division to improve the broadband interference suppression capability. To guarantee the communication performance meanwhile, it is required to reconstruct the subband signal to communication signal. In this paper, the combination of analog circuits and digital processing is used to build a subband division and signal reconstruction framework. The wide filtering in the first-stage is realized through analog filters to reduce the signal processing bandwidth. The narrow filtering in the second-stage is completed by digital filters to improve further the signal-to-noise ratio. This paper focusses on the problem of cross-subband reconstruction distortion in the communication signals’ subband division process. The time-frequency domain model of the subband division and signal reconstruction system is established to analyze the influence of the amplitude and phase inconsistency between subbands. To solve the inconsistency problem, the phase calibration method and the filter amplitude-frequency optimization method are proposed. The methods are to ensure the approximately distortion-free reconstruction of the cross-subband signal. Simulation and experiment results show that the amplitude-frequency response of the filter designed in the paper has good reconstruction accuracy. The phase calibration method solves the phase distortion problem of cross-subband signal reconstruction, and reduces effectively the bit error rate of reconstructed communication signals.
2023, 45(11): 4003-4015.
doi: 10.11999/JEIT230783
Abstract:
Automatic Modulation Classification (AMC) is essential for spectrum monitoring and cognitive radio. The Chirp Spread Spectrum (CSS) communication scheme could be developed remarkably due to its good anti-interference ability and robustness. However, research on the AMC of the CSS communication scheme is limited.Therefore, this paper proposes a CSS signal modulation classification method based on Multi-Feature Fusion (MFF) to enhance its recognition accuracy. This method which leverages spectrum and time-frequency map feature fusion learning and incorporates an attention module. The results of 11 types of CSS formats demonstrate that the proposed scheme exhibits superior recognition performance.
Automatic Modulation Classification (AMC) is essential for spectrum monitoring and cognitive radio. The Chirp Spread Spectrum (CSS) communication scheme could be developed remarkably due to its good anti-interference ability and robustness. However, research on the AMC of the CSS communication scheme is limited.Therefore, this paper proposes a CSS signal modulation classification method based on Multi-Feature Fusion (MFF) to enhance its recognition accuracy. This method which leverages spectrum and time-frequency map feature fusion learning and incorporates an attention module. The results of 11 types of CSS formats demonstrate that the proposed scheme exhibits superior recognition performance.
2023, 45(11): 4016-4025.
doi: 10.11999/JEIT230799
Abstract:
In order to improve the sum rate in the satellite communication system, power allocation in downlink of Asymmetric Paired Carrier Multiple Access (APCMA) system is investigated. Under the constraint of total power and the minimum quality of service for each user, the optimal power allocation scheme is obtained via the methods of convex optimization with the objective of maximizing the sum capacity, and two suboptimal power allocation schemes are given. Compared with the classic algorithm in Orthogonal Multiple Access (OMA), the simulation results show that the proposed scheme in APCMA maximizes the sum rate, and has superior performance in spectral efficiency.
In order to improve the sum rate in the satellite communication system, power allocation in downlink of Asymmetric Paired Carrier Multiple Access (APCMA) system is investigated. Under the constraint of total power and the minimum quality of service for each user, the optimal power allocation scheme is obtained via the methods of convex optimization with the objective of maximizing the sum capacity, and two suboptimal power allocation schemes are given. Compared with the classic algorithm in Orthogonal Multiple Access (OMA), the simulation results show that the proposed scheme in APCMA maximizes the sum rate, and has superior performance in spectral efficiency.
2023, 45(11): 4026-4032.
doi: 10.11999/JEIT230807
Abstract:
Waveform design is one of the critical technologies for achieving integrated sensing and communication, which is beneficial for alleviating the pressure of spectrum competition and saving resources. In this paper, a velocity measurement algorithm in Vehicle-to-everything(V2X) communications with IEEE 802.11ad wireless local area network waveform is proposed. Firstly, as the preamble in the physical layer frame structure has an ideal characteristic suitable for target sensing, the preambles of the received multi-frame signals are performed correlation operations at different moving steps, then the Doppler shift which is used for velocity measurement is obtained by converting Doppler frequency offset estimation into linear regression slope estimation. Secondly, in order to solve the problem of limited velocity measurement range caused by phase ambiguity, a phase compensation scheme is proposed. The simulation results show that the proposed algorithm can achieve centimeter-level accuracy in single target and LOS scenarios, and has lower velocity measurement error than the current similar algorithm.
Waveform design is one of the critical technologies for achieving integrated sensing and communication, which is beneficial for alleviating the pressure of spectrum competition and saving resources. In this paper, a velocity measurement algorithm in Vehicle-to-everything(V2X) communications with IEEE 802.11ad wireless local area network waveform is proposed. Firstly, as the preamble in the physical layer frame structure has an ideal characteristic suitable for target sensing, the preambles of the received multi-frame signals are performed correlation operations at different moving steps, then the Doppler shift which is used for velocity measurement is obtained by converting Doppler frequency offset estimation into linear regression slope estimation. Secondly, in order to solve the problem of limited velocity measurement range caused by phase ambiguity, a phase compensation scheme is proposed. The simulation results show that the proposed algorithm can achieve centimeter-level accuracy in single target and LOS scenarios, and has lower velocity measurement error than the current similar algorithm.
2023, 45(11): 4033-4040.
doi: 10.11999/JEIT230870
Abstract:
In the rapidly changing jamming environment, the transmission reliability of wireless communication systems can be significantly impacted. To enhance the transmission reliability of wireless communication systems under such fast-changing jamming conditions, a disturbance observer-based anti-jamming power control algorithm is proposed. The proposed algorithm first models the wireless communication system affected by jamming as a generalized stability control system and utilizes a disturbance observer to generate estimated values of the system state impacted by jamming. Subsequently, by using these estimated values to predict future tracking errors and steady-state control inputs, the algorithm optimizes the system's control strategy to achieve adaptive adjustments in response to the jamming environment. The simulation results demonstrate that, compared to conventional methods, the proposed algorithm can rapidly respond to changes in jamming, significantly improving the system’s transmission reliability under rapidly changing malicious jamming, and enhancing the system’s adaptability to jamming environments.
In the rapidly changing jamming environment, the transmission reliability of wireless communication systems can be significantly impacted. To enhance the transmission reliability of wireless communication systems under such fast-changing jamming conditions, a disturbance observer-based anti-jamming power control algorithm is proposed. The proposed algorithm first models the wireless communication system affected by jamming as a generalized stability control system and utilizes a disturbance observer to generate estimated values of the system state impacted by jamming. Subsequently, by using these estimated values to predict future tracking errors and steady-state control inputs, the algorithm optimizes the system's control strategy to achieve adaptive adjustments in response to the jamming environment. The simulation results demonstrate that, compared to conventional methods, the proposed algorithm can rapidly respond to changes in jamming, significantly improving the system’s transmission reliability under rapidly changing malicious jamming, and enhancing the system’s adaptability to jamming environments.
2023, 45(11): 4041-4049.
doi: 10.11999/JEIT230802
Abstract:
Considering the differential channels sensed by nodes and difficult network construction due to strong electromagnetic interference in wireless ad hoc networks, a multi-channel network construction algorithm based on hierarchical virtual clustering is proposed to realize network reliability improvement and interference control. Firstly, the similarity index is defined by the ratio of neighbors with common channels sensed by the adjacent nodes, which is utilized further to formulate the network modularity function. A clustering network is constructed with the largest modularity. Then, the cluster head nodes and gateway nodes are selected by the way of control before connection. The virtual backbone network controlled by R-hop Connected Dominating Set (CDS) is established by using the spanning tree method to provide routing and forwarding services for inter-cluster nodes. Finally, a restricted graph coloring method is proposed to implement inter-cluster and intra-cluster channel allocation to reduce the co-channel interference. Simulation results show that the proposed algorithm can obtain higher network modularity than the baseline schemes, while shows performance advantages in average cluster size and interference control.
Considering the differential channels sensed by nodes and difficult network construction due to strong electromagnetic interference in wireless ad hoc networks, a multi-channel network construction algorithm based on hierarchical virtual clustering is proposed to realize network reliability improvement and interference control. Firstly, the similarity index is defined by the ratio of neighbors with common channels sensed by the adjacent nodes, which is utilized further to formulate the network modularity function. A clustering network is constructed with the largest modularity. Then, the cluster head nodes and gateway nodes are selected by the way of control before connection. The virtual backbone network controlled by R-hop Connected Dominating Set (CDS) is established by using the spanning tree method to provide routing and forwarding services for inter-cluster nodes. Finally, a restricted graph coloring method is proposed to implement inter-cluster and intra-cluster channel allocation to reduce the co-channel interference. Simulation results show that the proposed algorithm can obtain higher network modularity than the baseline schemes, while shows performance advantages in average cluster size and interference control.
2023, 45(11): 4050-4059.
doi: 10.11999/JEIT230810
Abstract:
The aerial targets are usually far from the imaging system, making the imaged results have weak radiation intensity and limited imaging area. Especially when aerial target groups are distributed in a dense form, make further the imaged results have overlapping projection of such dense targets, and limit the performance of subsequent detection, track, and identification tasks. The array camera imaging system can provide complementary information about the target from multiple views and make effectively up for the deficiency of a single camera in detecting the resolution of nearby aerial targets. In this paper, the geometric relationship between nearby aerial targets and array cameras is studied and a super-resolution method for nearby targets based on sparse reconstruction of array camera images is proposed. Thanks to the prior assumption of sparsity of nearby aerial targets on the image plane and the transfer constraints between multiple views of array cameras regarding the target, relevant simulation experiments show that the proposed method can well super-resolve the obtained images of nearby targets and estimate effectively the position and number of nearby aerial targets.
The aerial targets are usually far from the imaging system, making the imaged results have weak radiation intensity and limited imaging area. Especially when aerial target groups are distributed in a dense form, make further the imaged results have overlapping projection of such dense targets, and limit the performance of subsequent detection, track, and identification tasks. The array camera imaging system can provide complementary information about the target from multiple views and make effectively up for the deficiency of a single camera in detecting the resolution of nearby aerial targets. In this paper, the geometric relationship between nearby aerial targets and array cameras is studied and a super-resolution method for nearby targets based on sparse reconstruction of array camera images is proposed. Thanks to the prior assumption of sparsity of nearby aerial targets on the image plane and the transfer constraints between multiple views of array cameras regarding the target, relevant simulation experiments show that the proposed method can well super-resolve the obtained images of nearby targets and estimate effectively the position and number of nearby aerial targets.
2023, 45(11): 4060-4071.
doi: 10.11999/JEIT230842
Abstract:
The Inter Satellite Links (ISL) is the key for China's Beidou-3 to overcome regional station deployment and achieve high-precision services. Its antenna Phase Center Offsets (PCO) is calibrated on the ground based on satellite mass and designed attitude when the equipment leaves the factory. However, fuel consumption, antenna deployment attitude, and other factors can cause changes in satellite mass and attitude during satellite launch, orbit entry, and in orbit stages, which will result in inconsistent values of antenna phase center deviation in orbit with ground calibration values. This change will be introduced as an error into the measurement value, thereby affecting the accuracy of satellite orbit determination. Therefore, this article studies the calibration method for the PCO of the inter-satellite links of in-orbit satellites. By combining with inter-satellite and satellite-ground observations, an in-orbit estimation method is established based on whole-network estimation. Two weeks of measured data are used to verify for all Medium Earth Orbit satellites (MEO) of Beidou-3, and a detailed analysis of in-orbit characteristics is conducted in conjunction with satellite manufacturers and orbital surfaces. Finally, its impact on the accuracy of orbit determination is verified. Results show that method proposed in this paper can effectively estimate the PCO of the inter-satellite links antenna in-orbit. It is found that the PCO of the inter-satellite links antenna in most in-orbit satellites is basically consistent with the values on the ground. However, C36, C37, C41, and C42 satellites have a deviation of about 15 cm from the ground calibration value in the Z-direction. Satellites C25, C26, C43 and C44 have opposite signs on the Y-direction, and there is a deviation of about 10 cm in the numerical value. Satellite C25, C26 have a deviation of nearly 30 cm in the Z-direction. After correctly calibrating the PCO of the inter-satellite links antenna in-orbit, the orbit accuracy can be improved by 15% compared to ground calibration products.
The Inter Satellite Links (ISL) is the key for China's Beidou-3 to overcome regional station deployment and achieve high-precision services. Its antenna Phase Center Offsets (PCO) is calibrated on the ground based on satellite mass and designed attitude when the equipment leaves the factory. However, fuel consumption, antenna deployment attitude, and other factors can cause changes in satellite mass and attitude during satellite launch, orbit entry, and in orbit stages, which will result in inconsistent values of antenna phase center deviation in orbit with ground calibration values. This change will be introduced as an error into the measurement value, thereby affecting the accuracy of satellite orbit determination. Therefore, this article studies the calibration method for the PCO of the inter-satellite links of in-orbit satellites. By combining with inter-satellite and satellite-ground observations, an in-orbit estimation method is established based on whole-network estimation. Two weeks of measured data are used to verify for all Medium Earth Orbit satellites (MEO) of Beidou-3, and a detailed analysis of in-orbit characteristics is conducted in conjunction with satellite manufacturers and orbital surfaces. Finally, its impact on the accuracy of orbit determination is verified. Results show that method proposed in this paper can effectively estimate the PCO of the inter-satellite links antenna in-orbit. It is found that the PCO of the inter-satellite links antenna in most in-orbit satellites is basically consistent with the values on the ground. However, C36, C37, C41, and C42 satellites have a deviation of about 15 cm from the ground calibration value in the Z-direction. Satellites C25, C26, C43 and C44 have opposite signs on the Y-direction, and there is a deviation of about 10 cm in the numerical value. Satellite C25, C26 have a deviation of nearly 30 cm in the Z-direction. After correctly calibrating the PCO of the inter-satellite links antenna in-orbit, the orbit accuracy can be improved by 15% compared to ground calibration products.
2023, 45(11): 4072-4082.
doi: 10.11999/JEIT230848
Abstract:
The electromagnetic space confrontation in electronic warfare is generally modeled as a zero-sum game. However, as the battlefield environment evolves, both sides of the game must adapt to new and unknown tasks, rendering manually designed game rules ineffective. A novel method called Population-based Multi-Agent Electromagnetic Countermeasure (PMAEC) is proposed to overcome the limitations of explicit game strategies. This approach enables the automatic generation of general electromagnetic countermeasure policies in unknown game paradigms. First, a meta-game framework is used to model the optimization problem of the electromagnetic countermeasure policy-population, which is decomposed into internal and external optimization based on electromagnetic game environments of the Multi-agent Combat Arena(MaCA) platform. Second, the meta-solver model is optimized by combining Auto-Curriculum Learning(ACL) with Meta-Learning technology. The PMAEC method involves iterative updates of the best response policy, expanding and strengthening the policy population to overcome the challenges leveraged by various difficult games. Simulation results of the MaCA platform demonstrate that the proposed method successfully bestows the meta-game with lower exploitability. Further, the trained population of electromagnetic countermeasure policies can be generalized to more complex zero-sum games. This approach extends the model from training based on simple scenarios to large-scale games in complex electromagnetic countermeasure environments, consequently enhancing the generalization capability of the strategies.
The electromagnetic space confrontation in electronic warfare is generally modeled as a zero-sum game. However, as the battlefield environment evolves, both sides of the game must adapt to new and unknown tasks, rendering manually designed game rules ineffective. A novel method called Population-based Multi-Agent Electromagnetic Countermeasure (PMAEC) is proposed to overcome the limitations of explicit game strategies. This approach enables the automatic generation of general electromagnetic countermeasure policies in unknown game paradigms. First, a meta-game framework is used to model the optimization problem of the electromagnetic countermeasure policy-population, which is decomposed into internal and external optimization based on electromagnetic game environments of the Multi-agent Combat Arena(MaCA) platform. Second, the meta-solver model is optimized by combining Auto-Curriculum Learning(ACL) with Meta-Learning technology. The PMAEC method involves iterative updates of the best response policy, expanding and strengthening the policy population to overcome the challenges leveraged by various difficult games. Simulation results of the MaCA platform demonstrate that the proposed method successfully bestows the meta-game with lower exploitability. Further, the trained population of electromagnetic countermeasure policies can be generalized to more complex zero-sum games. This approach extends the model from training based on simple scenarios to large-scale games in complex electromagnetic countermeasure environments, consequently enhancing the generalization capability of the strategies.
2023, 45(11): 4083-4091.
doi: 10.11999/JEIT230687
Abstract:
In recent years, low-altitude slow and small targets, such as Unmanned Aerial Vehicles (UAVs), have posed a great challenge to the management of existing low-altitude airspace. These targets have low echo Signal Noise Ratio (SNR) due to their low flight altitude, slow flight speed and small Radar Cross Section (RCS), which result in low detection probability and inaccurate parameter estimation by traditional detection and estimation methods based on Doppler information of target. In addition to the Doppler information generated by the radial motion of the target, the micro-Doppler information generated by the micro-motion parts of the target can also be used for the detection and estimation of low-altitude slow and small targets like UAVs, which is expected to improve the SNR of the target by aggregating the energy dispersed in multiple Doppler cells due to the micro-motion. In this paper, a joint Doppler and micro-Doppler detection and estimation method based on the Cardinality Balanced Multi-target Multi-Bernoulli (CBMeMBer) filter is proposed, which makes full usage of the Doppler and micro-Doppler information contained in the echoes of UAV targets. By jointly modelling the Doppler and micro-Doppler information of UAV targets under the framework of Random Finite Sets (RFS), effective integration and fusion of Doppler and micro-Doppler information can be achieved. This leads to a better detection and estimation performance of low-altitude slow and small targets. Simulation experiments show that the method can achieve stable detection and state estimation of UAV targets, and the detection sensitivity is improved by 2 dB compared with the traditional detection method that only uses target Doppler information.
In recent years, low-altitude slow and small targets, such as Unmanned Aerial Vehicles (UAVs), have posed a great challenge to the management of existing low-altitude airspace. These targets have low echo Signal Noise Ratio (SNR) due to their low flight altitude, slow flight speed and small Radar Cross Section (RCS), which result in low detection probability and inaccurate parameter estimation by traditional detection and estimation methods based on Doppler information of target. In addition to the Doppler information generated by the radial motion of the target, the micro-Doppler information generated by the micro-motion parts of the target can also be used for the detection and estimation of low-altitude slow and small targets like UAVs, which is expected to improve the SNR of the target by aggregating the energy dispersed in multiple Doppler cells due to the micro-motion. In this paper, a joint Doppler and micro-Doppler detection and estimation method based on the Cardinality Balanced Multi-target Multi-Bernoulli (CBMeMBer) filter is proposed, which makes full usage of the Doppler and micro-Doppler information contained in the echoes of UAV targets. By jointly modelling the Doppler and micro-Doppler information of UAV targets under the framework of Random Finite Sets (RFS), effective integration and fusion of Doppler and micro-Doppler information can be achieved. This leads to a better detection and estimation performance of low-altitude slow and small targets. Simulation experiments show that the method can achieve stable detection and state estimation of UAV targets, and the detection sensitivity is improved by 2 dB compared with the traditional detection method that only uses target Doppler information.
2023, 45(11): 4092-4100.
doi: 10.11999/JEIT230572
Abstract:
In order to improve the reliability and anti-jamming ability of information transmission for the Frequency-Hopping (FH) communication system, a Polar coding construction optimization method is proposed to adapt to the strong-jamming environment, which is based on a novel Polar coded slow FH communication system model. Firstly, the multi-objective reinforcement learning algorithm is designed for the hybrid channel containing normal state and jamming state, and then the information bit-channel sequence in the coding process is optimized. Consequently the error correction performance of the designed Polar codewords is improved. In addition, the complexity of algorithm is reduced by preprocessing the initialization and theoretically calculating the reward values. The simulation results show that the overall error performance of the proposed coding optimization method is better than those of conventional coding construction methods in the hybrid channel containing strong jamming. Compared with the 3rd Generation Partnership Project (3GPP) standard scheme in Fifth-Generation (5G) mobile communication systems, the obtained overall coding gain is up to 0.5 dB. Therefore the high-reliability and anti-jamming performance of Polar coded FH transmission is effectively improved.
In order to improve the reliability and anti-jamming ability of information transmission for the Frequency-Hopping (FH) communication system, a Polar coding construction optimization method is proposed to adapt to the strong-jamming environment, which is based on a novel Polar coded slow FH communication system model. Firstly, the multi-objective reinforcement learning algorithm is designed for the hybrid channel containing normal state and jamming state, and then the information bit-channel sequence in the coding process is optimized. Consequently the error correction performance of the designed Polar codewords is improved. In addition, the complexity of algorithm is reduced by preprocessing the initialization and theoretically calculating the reward values. The simulation results show that the overall error performance of the proposed coding optimization method is better than those of conventional coding construction methods in the hybrid channel containing strong jamming. Compared with the 3rd Generation Partnership Project (3GPP) standard scheme in Fifth-Generation (5G) mobile communication systems, the obtained overall coding gain is up to 0.5 dB. Therefore the high-reliability and anti-jamming performance of Polar coded FH transmission is effectively improved.
2023, 45(11): 4101-4109.
doi: 10.11999/JEIT221284
Abstract:
Focusing on the issue of multi-view High-Resolution Range Profile (HRRP) target recognition in an open set, a novel method based on Joint Dynamic Sparse Representation (JDSR) is presented. First, JDSR is used to solve the reconstruction error of multi-view HRRP on the over completed dictionary. The reconstruction error trails of matched and unmatched categories are modeled using Extreme Value Theory (EVT), and subsequently, the open-set recognition problem is transformed into a hypothesis test problem. The reconstruction error is used to determine candidate classes during the identification phase. The matched and nonmatched class scores are obtained based on the confidence level of the tail distribution, and their weighted sum is used to decide whether the inputs are from nonlibrary categories or candidate classes. The input HRRPs are obtained from the same target and can be used as useful information to improve recognition performance. The proposed method can effectively use such prior information for performance enhancement under the open-set condition. Moreover, performance can remain robust under multiview data acquisition scenarios. The HRRP data generated from MSTAR chips are used for the identification experiments, and the results reveal that the proposed method performs considerably better than some state-of-the-art methods.
Focusing on the issue of multi-view High-Resolution Range Profile (HRRP) target recognition in an open set, a novel method based on Joint Dynamic Sparse Representation (JDSR) is presented. First, JDSR is used to solve the reconstruction error of multi-view HRRP on the over completed dictionary. The reconstruction error trails of matched and unmatched categories are modeled using Extreme Value Theory (EVT), and subsequently, the open-set recognition problem is transformed into a hypothesis test problem. The reconstruction error is used to determine candidate classes during the identification phase. The matched and nonmatched class scores are obtained based on the confidence level of the tail distribution, and their weighted sum is used to decide whether the inputs are from nonlibrary categories or candidate classes. The input HRRPs are obtained from the same target and can be used as useful information to improve recognition performance. The proposed method can effectively use such prior information for performance enhancement under the open-set condition. Moreover, performance can remain robust under multiview data acquisition scenarios. The HRRP data generated from MSTAR chips are used for the identification experiments, and the results reveal that the proposed method performs considerably better than some state-of-the-art methods.
2023, 45(11): 4110-4116.
doi: 10.11999/JEIT230813
Abstract:
In dynamic collaborative networking systems such as radar and vehicular network systems, high precision time synchronization is a basic condition for the normal operation of these systems. However, in dynamic network systems and low interception scenarios, the time transfer signal is weak and dynamic simultaneously, and thus the time synchronization system has poor robustness and synchronization accuracy. Accordingly, it is necessary to improve the time synchronization accuracy in complex dynamic networking systems. The time transfer modem is the core device of the two-way time transfer system, and the tracking loop is a key part of it. The tracking loop can easily lose lock in complex conditions. To improve the robustness of the tracking loop, an Adaptive Kalman Filter (AKF) tracking algorithm is proposed. This tracking loop employs the adaptive factor to adjust the system noise covariance matrices to adapt to the variable input signal. The test results show that, compared with the traditional Phase Lock Loop (PLL) tracking method and the standard KF tracking loop, the proposed tracking loop shows better robustness and adaptability under weak signal and dynamic conditions. Moreover, the computational complexity of the proposed algorithm is not high. This algorithm is of great significance for improving the time synchronization accuracy of complex dynamic collaborative networking systems.
In dynamic collaborative networking systems such as radar and vehicular network systems, high precision time synchronization is a basic condition for the normal operation of these systems. However, in dynamic network systems and low interception scenarios, the time transfer signal is weak and dynamic simultaneously, and thus the time synchronization system has poor robustness and synchronization accuracy. Accordingly, it is necessary to improve the time synchronization accuracy in complex dynamic networking systems. The time transfer modem is the core device of the two-way time transfer system, and the tracking loop is a key part of it. The tracking loop can easily lose lock in complex conditions. To improve the robustness of the tracking loop, an Adaptive Kalman Filter (AKF) tracking algorithm is proposed. This tracking loop employs the adaptive factor to adjust the system noise covariance matrices to adapt to the variable input signal. The test results show that, compared with the traditional Phase Lock Loop (PLL) tracking method and the standard KF tracking loop, the proposed tracking loop shows better robustness and adaptability under weak signal and dynamic conditions. Moreover, the computational complexity of the proposed algorithm is not high. This algorithm is of great significance for improving the time synchronization accuracy of complex dynamic collaborative networking systems.
2023, 45(11): 4117-4126.
doi: 10.11999/JEIT230844
Abstract:
Global Navigation Satellite System(GNSS) time and frequency transfer has become the most widely used time and frequency transfer technique due to its fine uncertainty level and ease of use. Time and frequency transfer calibration is the key and necessary prerequisite for the accurate transfer of time and frequency values. The seperated absolute calibration technique suffers from complex calibration steps and multiple sources of uncertainty. To address these problems, an integrated absolute calibration technique with fewer implementation steps and fewer sources of uncertainty is proposed in this paper, i.e., an integrated one-time calibration of the BeiDou navigation Satellite system (BDS) time and frequency transfer chain, with lower measurement uncertainty. In this paper, through the research on the integrated absolute calibration method of time and frequency transfer chain, the integrated absolute calibration system and experimental platform of the time and frequency transfer chain are constructed, and the seperated absolute calibration and integrated absolute calibration experiments based on one actual BDS time and frequency transfer chain are realized and their uncertainties are evaluated. The results showed that the consistency of the calibration results under the two methods is better than 1.76 ns, and the synthetic standard uncertainties are 0.80 ns and 1.00 ns respectively.
Global Navigation Satellite System(GNSS) time and frequency transfer has become the most widely used time and frequency transfer technique due to its fine uncertainty level and ease of use. Time and frequency transfer calibration is the key and necessary prerequisite for the accurate transfer of time and frequency values. The seperated absolute calibration technique suffers from complex calibration steps and multiple sources of uncertainty. To address these problems, an integrated absolute calibration technique with fewer implementation steps and fewer sources of uncertainty is proposed in this paper, i.e., an integrated one-time calibration of the BeiDou navigation Satellite system (BDS) time and frequency transfer chain, with lower measurement uncertainty. In this paper, through the research on the integrated absolute calibration method of time and frequency transfer chain, the integrated absolute calibration system and experimental platform of the time and frequency transfer chain are constructed, and the seperated absolute calibration and integrated absolute calibration experiments based on one actual BDS time and frequency transfer chain are realized and their uncertainties are evaluated. The results showed that the consistency of the calibration results under the two methods is better than 1.76 ns, and the synthetic standard uncertainties are 0.80 ns and 1.00 ns respectively.
2023, 45(11): 4127-4136.
doi: 10.11999/JEIT230806
Abstract:
The railway time synchronization network provides the standard time quantity value for various railway systems. The accuracy and stability of the time quantity value have an important impact on the safe and the efficient operation of the railway systems. There are three potential problems with the current railway time synchronization network. The traceability references of each time node are inconsistent, and the time of each node is not accurately traced to Coordinated Universal Time (UTC). Only one primary time node is set. The secondary and the tertiary time nodes are greatly affected by the failure of the primary time node, and lack of robustness. Monitoring methods are only used a single time node. There is no automatic monitoring method at the overall level. In view of the above potential problems, the distributed Ensemble Time scale (TE) for railway time synchronization network that can accurately trace to UTC is proposed. A simulation model of railway time synchronization network is established, and a TE algorithm is designed. TE is generated by 19 atomic clocks from the primary and the secondary time nodes. The results show that the time differences between TE and UTC can be better than 30 ns. The uncertainty of TE-UTC is better than 5 ns. When the primary time node works normally, the time stability of the secondary time node can be improved about 40% by introducing TE. When the primary time node fails, TE can be continuously generated and used as a unified traceability reference. The frequency and time stability of the secondary time node under the TE synchronization architecture is about 35% higher than that under the traditional synchronization architecture. The time differences between any time nodes can be obtained based on TE. By analyzing the time differences data, automatic monitoring of all time nodes and the continuity of Precision Time Protocol (PTP) links at the overall level can be realized.
The railway time synchronization network provides the standard time quantity value for various railway systems. The accuracy and stability of the time quantity value have an important impact on the safe and the efficient operation of the railway systems. There are three potential problems with the current railway time synchronization network. The traceability references of each time node are inconsistent, and the time of each node is not accurately traced to Coordinated Universal Time (UTC). Only one primary time node is set. The secondary and the tertiary time nodes are greatly affected by the failure of the primary time node, and lack of robustness. Monitoring methods are only used a single time node. There is no automatic monitoring method at the overall level. In view of the above potential problems, the distributed Ensemble Time scale (TE) for railway time synchronization network that can accurately trace to UTC is proposed. A simulation model of railway time synchronization network is established, and a TE algorithm is designed. TE is generated by 19 atomic clocks from the primary and the secondary time nodes. The results show that the time differences between TE and UTC can be better than 30 ns. The uncertainty of TE-UTC is better than 5 ns. When the primary time node works normally, the time stability of the secondary time node can be improved about 40% by introducing TE. When the primary time node fails, TE can be continuously generated and used as a unified traceability reference. The frequency and time stability of the secondary time node under the TE synchronization architecture is about 35% higher than that under the traditional synchronization architecture. The time differences between any time nodes can be obtained based on TE. By analyzing the time differences data, automatic monitoring of all time nodes and the continuity of Precision Time Protocol (PTP) links at the overall level can be realized.
2023, 45(11): 4137-4149.
doi: 10.11999/JEIT230837
Abstract:
To solve the problem of distinguishing highly-concealed synchronous spoofing signals from authentic signals inside a GPS receiver, a spoofing identification method based on clustering analysis of multiple characteristics is proposed. The procedure of baseband anti-spoofing processing is summarized. On the basis of spoofing detection and signal parameter estimation, the Code-Carrier Doppler frequency Coherence (CCDC), relative amplitude, and carrier-to-noise ratio variation characteristics are extracted as the spoofing identification characteristics at the signal processing level. At the information processing level, the pseudo-range residual corresponding to the combination of different signal components and the receiver clock variation before and after the spoofing attack are calculated. Then the K-means clustering is used to identify the spoofing signal combining these characteristics. The semi-physical experiment based on Radio Frequency (RF) signal sampling and playback and the processing results of our anti-spoofing software receiver demonstrate that the proposed method can identify synchronous spoofing timely and accurately, thus guiding the receiver to mitigate the effects of spoofing and recover correct navigation solutions.
To solve the problem of distinguishing highly-concealed synchronous spoofing signals from authentic signals inside a GPS receiver, a spoofing identification method based on clustering analysis of multiple characteristics is proposed. The procedure of baseband anti-spoofing processing is summarized. On the basis of spoofing detection and signal parameter estimation, the Code-Carrier Doppler frequency Coherence (CCDC), relative amplitude, and carrier-to-noise ratio variation characteristics are extracted as the spoofing identification characteristics at the signal processing level. At the information processing level, the pseudo-range residual corresponding to the combination of different signal components and the receiver clock variation before and after the spoofing attack are calculated. Then the K-means clustering is used to identify the spoofing signal combining these characteristics. The semi-physical experiment based on Radio Frequency (RF) signal sampling and playback and the processing results of our anti-spoofing software receiver demonstrate that the proposed method can identify synchronous spoofing timely and accurately, thus guiding the receiver to mitigate the effects of spoofing and recover correct navigation solutions.
2023, 45(11): 4150-4160.
doi: 10.11999/JEIT230834
Abstract:
In order to solve the problem that the Global Navigation Satellite System (GNSS) signal is frequently unlocked or rejected in complex urban environment, which has great influence on the navigation accuracy and robustness of GNSS/ Strapdown Inertial Navigation System (SINS) integrated navigation system, an improved factor graph filtering method is proposed in this paper. Firstly, GNSS receiver internal parameters are used to construct signal error identification function to estimate the performance of signal measurement at real time in the situation of multipath interference and occlusion. Simultaneously, zero-velocity update factor is constructed by the carrier motion constraint to update the system state under the condition of GNSS rejection. The experimental results show that compared with the classical factor graph method, the improved factor graph method can improve the positioning accuracy by 63.50% and the velocity measurement accuracy by 42.26% in complex environment with lower storage and computational complexity. The method is especially suitable for the scenarios with strong constraints on navigation accuracy, hardware resources and real-time performance in urban vehicle assisted driving navigation equipment.
In order to solve the problem that the Global Navigation Satellite System (GNSS) signal is frequently unlocked or rejected in complex urban environment, which has great influence on the navigation accuracy and robustness of GNSS/ Strapdown Inertial Navigation System (SINS) integrated navigation system, an improved factor graph filtering method is proposed in this paper. Firstly, GNSS receiver internal parameters are used to construct signal error identification function to estimate the performance of signal measurement at real time in the situation of multipath interference and occlusion. Simultaneously, zero-velocity update factor is constructed by the carrier motion constraint to update the system state under the condition of GNSS rejection. The experimental results show that compared with the classical factor graph method, the improved factor graph method can improve the positioning accuracy by 63.50% and the velocity measurement accuracy by 42.26% in complex environment with lower storage and computational complexity. The method is especially suitable for the scenarios with strong constraints on navigation accuracy, hardware resources and real-time performance in urban vehicle assisted driving navigation equipment.
2023, 45(11): 4161-4169.
doi: 10.11999/JEIT230796
Abstract:
This paper investigates the construction of dynamic electromagnetic spectrum maps using a limited amount of monitored sample data. First, the time-varying spectrum maps of the dynamic electromagnetic environment are modeled as three-dimensional spectrum tensors. The tensor Tucker decomposition is then employed to extract low-dimensional features, including physically meaningful core tensors and factor matrices. Second, a low-rank tensor completion model based on the Tucker decomposition is designed considering the correlation between the temporal, spatial, and frequency domains of the spectrum tensorand and the sparsity of the monitored sample data. This model transforms the spectrum map construction task into an optimization problem of completing low-rank tensors with missing data. To address this problem, this paper proposes two spectrum map construction algorithms that do not rely on prior information: high-precision and fast spectrum map construction algorithms. The former employs an alternating least squares method for iteratively solving the core tensor and factor matrices, achieving high-precision spectrum map construction through a “completion-decomposition” process. Meanwhile, the latter employs a sequential truncated higher-order singular value decomposition method for averaging multiple low-rank approximate tensors, offering rapid convergence and low computational complexity. Therefore, this algorithm can quickly construct spectrum maps by sacrificing a small amount of construction accuracy. The simulation results show that the proposed algorithms can accurately construct spectrum maps and outperform comparative algorithms in terms of construction accuracy, runtime consumption, and noise robustness.
This paper investigates the construction of dynamic electromagnetic spectrum maps using a limited amount of monitored sample data. First, the time-varying spectrum maps of the dynamic electromagnetic environment are modeled as three-dimensional spectrum tensors. The tensor Tucker decomposition is then employed to extract low-dimensional features, including physically meaningful core tensors and factor matrices. Second, a low-rank tensor completion model based on the Tucker decomposition is designed considering the correlation between the temporal, spatial, and frequency domains of the spectrum tensorand and the sparsity of the monitored sample data. This model transforms the spectrum map construction task into an optimization problem of completing low-rank tensors with missing data. To address this problem, this paper proposes two spectrum map construction algorithms that do not rely on prior information: high-precision and fast spectrum map construction algorithms. The former employs an alternating least squares method for iteratively solving the core tensor and factor matrices, achieving high-precision spectrum map construction through a “completion-decomposition” process. Meanwhile, the latter employs a sequential truncated higher-order singular value decomposition method for averaging multiple low-rank approximate tensors, offering rapid convergence and low computational complexity. Therefore, this algorithm can quickly construct spectrum maps by sacrificing a small amount of construction accuracy. The simulation results show that the proposed algorithms can accurately construct spectrum maps and outperform comparative algorithms in terms of construction accuracy, runtime consumption, and noise robustness.
2023, 45(11): 4170-4178.
doi: 10.11999/JEIT230862
Abstract:
Considering the monitoring of space targets in high orbit, the waveform design of the distributed coherent radar system is studied. The core goal is to take into account the large time-bandwidth of the signal under the premise of ensuring good waveform orthogonality. In this paper, a compound modulation waveform of intrapulse step frequency and phase encoding is proposed. Firstly, the time domain expression of the intrapulse step frequency-phase encoding signal is given, and then its ambiguity function and autocorrelation main peak amplitude are deduced. Secondly, the concept of cyclic code is introduced, and finally the simulation results of intrapulse step frequency-cyclic phase coded signal are compared with other signals. The simulation results show that, compared with the single modulation signal and the pulse-to-pulse modulation signal, the intra-pulse step frequency-cyclic phase coding signal has better orthogonality, and at the same time ensures a large bandwidth of the signal. It provides a good theoretical support for the follow-up research work of distributed coherent radar.
Considering the monitoring of space targets in high orbit, the waveform design of the distributed coherent radar system is studied. The core goal is to take into account the large time-bandwidth of the signal under the premise of ensuring good waveform orthogonality. In this paper, a compound modulation waveform of intrapulse step frequency and phase encoding is proposed. Firstly, the time domain expression of the intrapulse step frequency-phase encoding signal is given, and then its ambiguity function and autocorrelation main peak amplitude are deduced. Secondly, the concept of cyclic code is introduced, and finally the simulation results of intrapulse step frequency-cyclic phase coded signal are compared with other signals. The simulation results show that, compared with the single modulation signal and the pulse-to-pulse modulation signal, the intra-pulse step frequency-cyclic phase coding signal has better orthogonality, and at the same time ensures a large bandwidth of the signal. It provides a good theoretical support for the follow-up research work of distributed coherent radar.
2023, 45(11): 4179-4189.
doi: 10.11999/JEIT230808
Abstract:
Ultra-WideBand (UWB) technology is widely used for indoor positioning due to its advantages of large bandwidth, low power, and high precision. However, since UWB is essentially a communication signal system and it is difficult to form a network in complex environments, UWB systems still face challenges in complex indoor environments such as underground. To address this issue, high concurrency and coverage Navigation UWB(Hnav-UWB) is proposed in this paper based on the UWB standard signal system. The frame structure is simplified by optimizing the redundancy of communication information, the pulse transmission frequency is reduced and the energy of each pulse is increased, and an improved Time Hopping Binary Phase Shift Keying (TH-BPSK) modulation method is adopted to enhance the signal’s multi-user and multipath capabilities. Moreover, a dynamic reconstruction node network is designed in this paper to adapt to complex environments. The network has no master-slave nodes, pairwise distances are obtained by bidirectional ranging, relative position coordinates are built by using the MultiDimensional Scaling(MDS) algorithm, accuracy is improved by using the Distributed Cooperative Localization(DCL) algorithm, and map matching is performed by using the Least Squares(LS) method based on the known position of a point on the map. Based on the self-built Impulse-Radio Ultra-WideBand (IR-UWB) simulation system experiment, the results show that under the same conditions, Hnav-UWB’s bit error rate is 10 times lower than that of the control group, and the positioning accuracy is improved by 3 times. After 1 000 Monte Carlo simulations, the matching accuracy of the dynamic reconstruction node network reaches 95%.
Ultra-WideBand (UWB) technology is widely used for indoor positioning due to its advantages of large bandwidth, low power, and high precision. However, since UWB is essentially a communication signal system and it is difficult to form a network in complex environments, UWB systems still face challenges in complex indoor environments such as underground. To address this issue, high concurrency and coverage Navigation UWB(Hnav-UWB) is proposed in this paper based on the UWB standard signal system. The frame structure is simplified by optimizing the redundancy of communication information, the pulse transmission frequency is reduced and the energy of each pulse is increased, and an improved Time Hopping Binary Phase Shift Keying (TH-BPSK) modulation method is adopted to enhance the signal’s multi-user and multipath capabilities. Moreover, a dynamic reconstruction node network is designed in this paper to adapt to complex environments. The network has no master-slave nodes, pairwise distances are obtained by bidirectional ranging, relative position coordinates are built by using the MultiDimensional Scaling(MDS) algorithm, accuracy is improved by using the Distributed Cooperative Localization(DCL) algorithm, and map matching is performed by using the Least Squares(LS) method based on the known position of a point on the map. Based on the self-built Impulse-Radio Ultra-WideBand (IR-UWB) simulation system experiment, the results show that under the same conditions, Hnav-UWB’s bit error rate is 10 times lower than that of the control group, and the positioning accuracy is improved by 3 times. After 1 000 Monte Carlo simulations, the matching accuracy of the dynamic reconstruction node network reaches 95%.
2023, 45(11): 4190-4202.
doi: 10.11999/JEIT221301
Abstract:
Passive sonar detects targets by receiving radiated noise signals emitted from the targets. Underwater acoustic target recognition is an important research area in the underwater acoustic engineering field to identify individual targets by analyzing underwater acoustic signals. As a research hotspot in various fields in recent years, deep learning has attracted considerable attention from scholars for its application to the underwater acoustic target recognition field. Based on the step framework of underwater acoustic target recognition, two typical deep network models are introduced. Herein, two major implications of deep learning in the underwater acoustic target recognition field are summarized. The key issues and research progress in recent years are investigated for deep learning as a classifier based on features such as spectrograms and mel-frequency cepstrum coefficient and for deep learning as a signal processing tool based on signal processing methods such as data enhancement and data denoising. The development trend of this field is explored from three aspects, namely, data-driven, feature-driven, and model-driven, to promote the development of underwater acoustic target recognition.
Passive sonar detects targets by receiving radiated noise signals emitted from the targets. Underwater acoustic target recognition is an important research area in the underwater acoustic engineering field to identify individual targets by analyzing underwater acoustic signals. As a research hotspot in various fields in recent years, deep learning has attracted considerable attention from scholars for its application to the underwater acoustic target recognition field. Based on the step framework of underwater acoustic target recognition, two typical deep network models are introduced. Herein, two major implications of deep learning in the underwater acoustic target recognition field are summarized. The key issues and research progress in recent years are investigated for deep learning as a classifier based on features such as spectrograms and mel-frequency cepstrum coefficient and for deep learning as a signal processing tool based on signal processing methods such as data enhancement and data denoising. The development trend of this field is explored from three aspects, namely, data-driven, feature-driven, and model-driven, to promote the development of underwater acoustic target recognition.
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