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2015 Vol. 37, No. 10
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3-D Reconstruction for Multi-channel SAR InterferometryUsing Terrain Stagnation Point Based Division
2015, 37(10): 2287-2293.
doi: 10.11999/JEIT150244
Abstract:
Multi-channel SAR can reconstruct the 3-D surface of the observed scene with its resolution power in the elevation. However, with limited baseline length, most methods suffer from limited precision and significant miss rates. In view of this situation, a new 3-D reconstruction method using terrain stagnation point based division is proposed. Firstly, 3-D distribution is obtained using tomography; secondly, stagnation point position and division are conducted to separate the layover; then 3-D reconstruction is conducted using interferometry. This method combines the resolving power of multi-channel SAR and high precision of interferometry. Therefore, reconstruction results with higher precision and greater stability are achieved. The effectiveness of the method is validated using experiments with simulated data.
Multi-channel SAR can reconstruct the 3-D surface of the observed scene with its resolution power in the elevation. However, with limited baseline length, most methods suffer from limited precision and significant miss rates. In view of this situation, a new 3-D reconstruction method using terrain stagnation point based division is proposed. Firstly, 3-D distribution is obtained using tomography; secondly, stagnation point position and division are conducted to separate the layover; then 3-D reconstruction is conducted using interferometry. This method combines the resolving power of multi-channel SAR and high precision of interferometry. Therefore, reconstruction results with higher precision and greater stability are achieved. The effectiveness of the method is validated using experiments with simulated data.
2015, 37(10): 2294-2299.
doi: 10.11999/JEIT141576
Abstract:
The numerical calculation of forward scatter Shadow Inverse Synthetic Aperture Radar (SISAR) imaging is usually performed by the Fresnel numerical integral which is complicated and time consuming. To improve the calculation speed, the fast SISAR imaging method is investigated. Firstly, a fast imaging method based on the Fast Fourier Transform (FFT) is proposed while the phase errors introduced by the FFT are compensated. Then, through the analysis of the spectrum on the motion compensated signal, the sampling law for SISAR imaging is given, indicating that signals used for imaging can be sampled at a rate much lower than the Nyquist sampling rate. Simulation results show that the proposed fast imaging method can give accurate profiles and significantly reduce the computation, which is of practical meaning in engineering application.
The numerical calculation of forward scatter Shadow Inverse Synthetic Aperture Radar (SISAR) imaging is usually performed by the Fresnel numerical integral which is complicated and time consuming. To improve the calculation speed, the fast SISAR imaging method is investigated. Firstly, a fast imaging method based on the Fast Fourier Transform (FFT) is proposed while the phase errors introduced by the FFT are compensated. Then, through the analysis of the spectrum on the motion compensated signal, the sampling law for SISAR imaging is given, indicating that signals used for imaging can be sampled at a rate much lower than the Nyquist sampling rate. Simulation results show that the proposed fast imaging method can give accurate profiles and significantly reduce the computation, which is of practical meaning in engineering application.
2015, 37(10): 2300-2306.
doi: 10.11999/JEIT141631
Abstract:
In order to solve the problem of range side-lobes suppression performance degradation due to error between scatter and sample center of tradition methods, a new adaptive pulse compression algorithm based on Reiterative Linearly Constrained Minimum Variance (RLCMV) is presented in this paper. Firstly, adaptive beamformer is introduced into adaptive pulse compression. Then, linearly constraint is forced on range bins of target and interference, and diagonal loading techniques are applied. Finally, reiterative method is presented to suppress the side-lobe of target in range of different Radar Cross Section (RCS). Simulation results show that this algorithm can effectively suppress side-lobes of scatters random distributed in range bin, and it is robust to error between scatters and sample center. It keeps excellent performance even in multi-targets and range- extended target scenario, and improves performance of high Doppler target to a certain extend.
In order to solve the problem of range side-lobes suppression performance degradation due to error between scatter and sample center of tradition methods, a new adaptive pulse compression algorithm based on Reiterative Linearly Constrained Minimum Variance (RLCMV) is presented in this paper. Firstly, adaptive beamformer is introduced into adaptive pulse compression. Then, linearly constraint is forced on range bins of target and interference, and diagonal loading techniques are applied. Finally, reiterative method is presented to suppress the side-lobe of target in range of different Radar Cross Section (RCS). Simulation results show that this algorithm can effectively suppress side-lobes of scatters random distributed in range bin, and it is robust to error between scatters and sample center. It keeps excellent performance even in multi-targets and range- extended target scenario, and improves performance of high Doppler target to a certain extend.
2015, 37(10): 2307-2313.
doi: 10.11999/JEIT141591
Abstract:
Most traditional recognition methods for High Resolution Range Profile (HRRP) only utilize the amplitude information and need large number of training samples to obtain better estimation precision of model parameters. To utilize the phase information contained in the complex echoes and obtain better recognition performance with small training data and low sampling rate, a statistical model based on Multi-Task Leaning (MTL) and Complex Factor Analysis (CFA), referred to as MTL-CFA, is proposed in this paper. The MTL-CFA model directly describes the complex HRRP data. The statistical modeling of each training aspect-frame is considered as a single task, and all tasks share a common loading matrix. The factor number of each task is automatically determined via the Beta-Bernoulli sparse prior. Experimental results based on measured data show that the proposed model MTL-CFA can not only describe the observed data with lower order of model complexity, but also obtain satisfactory recognition accuracy with small training data, compared with the traditional Single- Task Learning (STL) based on FA models.
Most traditional recognition methods for High Resolution Range Profile (HRRP) only utilize the amplitude information and need large number of training samples to obtain better estimation precision of model parameters. To utilize the phase information contained in the complex echoes and obtain better recognition performance with small training data and low sampling rate, a statistical model based on Multi-Task Leaning (MTL) and Complex Factor Analysis (CFA), referred to as MTL-CFA, is proposed in this paper. The MTL-CFA model directly describes the complex HRRP data. The statistical modeling of each training aspect-frame is considered as a single task, and all tasks share a common loading matrix. The factor number of each task is automatically determined via the Beta-Bernoulli sparse prior. Experimental results based on measured data show that the proposed model MTL-CFA can not only describe the observed data with lower order of model complexity, but also obtain satisfactory recognition accuracy with small training data, compared with the traditional Single- Task Learning (STL) based on FA models.
2015, 37(10): 2314-2320.
doi: 10.11999/JEIT150159
Abstract:
In order to solve the problem that the power is transmitted dispersedly in traditional bistatic MIMO radar, a method about the transmit power focus of the bistatic MIMO radar is proposed. Firstly, the mathematic model is constructed based on an effective optimal criterion that can not only constrain the maximum error of the optimal beam and the desire one less than the given value, but also minimize the peak side lobe power of the transmit pattern. At the same time, a special beam matrix of transmitting terminal is constructed, not only making equivalent transmit/receive steering vector possessing the character of rotational invariance property, but also simplifying the original optimized model in order to be fast solved via second-order cone programming theory. Secondly, the transmitting and receiving angle of space target is estimated by utilizing improved PARallel FACtor (PARFAC) algorithm. The initial iteration point in the least square algorithm of PARFAC interior is improved by integrating into rotation invariance of transmitting/receiving steering vector, which can effectively decrease the number of iteration. Furthermore, the Cramer-Rao Bound of multi-target angle estimation under bistatic MIMO radar transmitting power focusing is derived which prove the superiority of the proposed method. Finally, the simulation results show the effectiveness of the theoretical analysis.
In order to solve the problem that the power is transmitted dispersedly in traditional bistatic MIMO radar, a method about the transmit power focus of the bistatic MIMO radar is proposed. Firstly, the mathematic model is constructed based on an effective optimal criterion that can not only constrain the maximum error of the optimal beam and the desire one less than the given value, but also minimize the peak side lobe power of the transmit pattern. At the same time, a special beam matrix of transmitting terminal is constructed, not only making equivalent transmit/receive steering vector possessing the character of rotational invariance property, but also simplifying the original optimized model in order to be fast solved via second-order cone programming theory. Secondly, the transmitting and receiving angle of space target is estimated by utilizing improved PARallel FACtor (PARFAC) algorithm. The initial iteration point in the least square algorithm of PARFAC interior is improved by integrating into rotation invariance of transmitting/receiving steering vector, which can effectively decrease the number of iteration. Furthermore, the Cramer-Rao Bound of multi-target angle estimation under bistatic MIMO radar transmitting power focusing is derived which prove the superiority of the proposed method. Finally, the simulation results show the effectiveness of the theoretical analysis.
2015, 37(10): 2321-2327.
doi: 10.11999/JEIT150187
Abstract:
Focusing on the range ambiguity of the moving target in airborne radar system, a novel Space-Time Adaptive Processing (STAP) approach based on frequency diverse array configuration is proposed for range ambiguous clutter suppression. In the proposed method, the controllable degree-of-freedom is exploited, which is introduced by the frequency diverse. The range ambiguity number is incorporated into the steering vector of the target signal. By separating the different range ambiguous range region in the spatial frequency domain, the target can be detected separately within each range region and thus range ambiguity can be resolved. By using the proposed method, giving only one pulse repetition frequency, the moving target can be detected and the range ambiguity can be resolved simultaneously, which improves the performance of airborne radar evidently. Simulation results demonstrate the effectiveness of the proposed method.
Focusing on the range ambiguity of the moving target in airborne radar system, a novel Space-Time Adaptive Processing (STAP) approach based on frequency diverse array configuration is proposed for range ambiguous clutter suppression. In the proposed method, the controllable degree-of-freedom is exploited, which is introduced by the frequency diverse. The range ambiguity number is incorporated into the steering vector of the target signal. By separating the different range ambiguous range region in the spatial frequency domain, the target can be detected separately within each range region and thus range ambiguity can be resolved. By using the proposed method, giving only one pulse repetition frequency, the moving target can be detected and the range ambiguity can be resolved simultaneously, which improves the performance of airborne radar evidently. Simulation results demonstrate the effectiveness of the proposed method.
2015, 37(10): 2328-2334.
doi: 10.11999/JEIT150153
Abstract:
An adaptive Bayesian super-resolution imaging algorithm based on the combined multiple frames data is proposed to enhance the azimuth resolution of airborne single-channel forward-looking radar. The echo of the forward-looking radar in the Gaussian noise is modeled, and the processing space is expanded from the low dimension of single frame data to the high dimension of multiple frames data to enhance the sparsity of domain scatterers. During the framework, the sparsity of the scatterers is modeled in spatial domain, and the imaging is converted into a problem of signal optimization based on Bayesian formalism. The final optimal result can be solved by the conjugate gradient method. In this framework, the statistic parameter is estimated with data-driven. Simulation results demonstrate that the proposed algorithm both can increase the resolution of the forward-looking imaging results and suppress the artifacts.
An adaptive Bayesian super-resolution imaging algorithm based on the combined multiple frames data is proposed to enhance the azimuth resolution of airborne single-channel forward-looking radar. The echo of the forward-looking radar in the Gaussian noise is modeled, and the processing space is expanded from the low dimension of single frame data to the high dimension of multiple frames data to enhance the sparsity of domain scatterers. During the framework, the sparsity of the scatterers is modeled in spatial domain, and the imaging is converted into a problem of signal optimization based on Bayesian formalism. The final optimal result can be solved by the conjugate gradient method. In this framework, the statistic parameter is estimated with data-driven. Simulation results demonstrate that the proposed algorithm both can increase the resolution of the forward-looking imaging results and suppress the artifacts.
Application of Phase Diagram to Sampling Ratio Analysis in Sparse Microwave Imaging Change Detection
2015, 37(10): 2335-2341.
doi: 10.11999/JEIT150272
Abstract:
Phase diagram is an important method to evaluate sparse microwave imaging radar performance. Phase transition boundary can characterize the trend of accurate recovery rate visibly and clearly in terms of varied SNR, sparsity and sampling ratio. In sparse microwave imaging change detection, the small variation can be accurately extracted from multiple observations using distributed compressed sensing theory for the sparse scene. Phase diagram is introduced to evaluate the performance of change detection in different sampling ratio under the conditions that the sparsity and SNR has little change. Phase diagram can be used to describe the trend of phase transition boundary and to determine the data collection bounds. Furthermore, a series of simulations and experiments are conducted to verify the practicability of phase diagram. It is available to reduce the measurements and complexity of the sparse microwave imaging system.
Phase diagram is an important method to evaluate sparse microwave imaging radar performance. Phase transition boundary can characterize the trend of accurate recovery rate visibly and clearly in terms of varied SNR, sparsity and sampling ratio. In sparse microwave imaging change detection, the small variation can be accurately extracted from multiple observations using distributed compressed sensing theory for the sparse scene. Phase diagram is introduced to evaluate the performance of change detection in different sampling ratio under the conditions that the sparsity and SNR has little change. Phase diagram can be used to describe the trend of phase transition boundary and to determine the data collection bounds. Furthermore, a series of simulations and experiments are conducted to verify the practicability of phase diagram. It is available to reduce the measurements and complexity of the sparse microwave imaging system.
2015, 37(10): 2342-2348.
doi: 10.11999/JEIT141577
Abstract:
Sea surface salinity remote sensing is seriously impacted by Radio Frequency Interference (RFI) over coastal areas, detecting RFI sources and analyzing its influence characteristic for developing RFI suppression research in the nearshore areas is of great significance. Based on the unique multi-angle observation imaging and polarization characteristics of the SMOS satellite sensor MIRAS, this paper generates the RFI sources distribution diagram and analyzes its distribution characteristics and influence scope through synthesis third and fouth Stokes parameters in the China sea. The results indicate that the RFI sources are concentrated distributed throughout coastal land areas of the Bohai sea, the Yellow sea, the west of the East China Sea and the north of the south China sea are strong impacted by RFI sources, and the sources have big different effects on ascending pass and descending pass data. The RFI sources may be microwave emission station, displaying as pointlike radio source, and the strong sources can pollute satellite data within a few hundred kilometers through antenna sidelobes, and RFI suppression is a scientific problem right now for the reason that RFI has complex effects on satellite depending on different attenuation and antenna radiation patterns.
Sea surface salinity remote sensing is seriously impacted by Radio Frequency Interference (RFI) over coastal areas, detecting RFI sources and analyzing its influence characteristic for developing RFI suppression research in the nearshore areas is of great significance. Based on the unique multi-angle observation imaging and polarization characteristics of the SMOS satellite sensor MIRAS, this paper generates the RFI sources distribution diagram and analyzes its distribution characteristics and influence scope through synthesis third and fouth Stokes parameters in the China sea. The results indicate that the RFI sources are concentrated distributed throughout coastal land areas of the Bohai sea, the Yellow sea, the west of the East China Sea and the north of the south China sea are strong impacted by RFI sources, and the sources have big different effects on ascending pass and descending pass data. The RFI sources may be microwave emission station, displaying as pointlike radio source, and the strong sources can pollute satellite data within a few hundred kilometers through antenna sidelobes, and RFI suppression is a scientific problem right now for the reason that RFI has complex effects on satellite depending on different attenuation and antenna radiation patterns.
2015, 37(10): 2349-2355.
doi: 10.11999/JEIT150200
Abstract:
In order to prove the inverse windowing algorithm is a complete reconstruction algorithm, the inverse windowing algorithm is analyzed, through the method that the completely different inverse windowing algorithm and overlapping windowing algorithm are combined into the same mathematical model of SNR; equivalent model is established, the SNR loss of equivalent model is deduced by signal reconstruction theory, which demonstrates that inverse windowing algorithm is a kind of perfect reconstruction algorithm, so the idea is proposed that it is necessary for inverse windowing algorithm to use under conditions of incomplete reconstruction. Compared windowing effects between Hanning window and Blackman window in DSSS which contains narrow-band interference, error rate is simulated, which proves the correctness of this article conclusion. Interference suppression scheme is proposed.
In order to prove the inverse windowing algorithm is a complete reconstruction algorithm, the inverse windowing algorithm is analyzed, through the method that the completely different inverse windowing algorithm and overlapping windowing algorithm are combined into the same mathematical model of SNR; equivalent model is established, the SNR loss of equivalent model is deduced by signal reconstruction theory, which demonstrates that inverse windowing algorithm is a kind of perfect reconstruction algorithm, so the idea is proposed that it is necessary for inverse windowing algorithm to use under conditions of incomplete reconstruction. Compared windowing effects between Hanning window and Blackman window in DSSS which contains narrow-band interference, error rate is simulated, which proves the correctness of this article conclusion. Interference suppression scheme is proposed.
2015, 37(10): 2356-2362.
doi: 10.11999/JEIT150328
Abstract:
In order to select the optimal pulsars combination for X-ray Pulsar NAVigation (XPNAV), the influence factors of visibility, quality and space distribution of pulsars are studied. Besides, constraint equations for visibility based on the restrictions of celestial bodys shadow, X-ray disturbance source and detectors angle of view are built respectively; an evaluation equation for quality factor based on Cramer-Rao low bound is analyzed; the method for calculating Weighted Dilution Of Precision (WDOP), which decreases as the number of observable pulsars increases, is researched. Finally, a method for selecting pulsars based on looking up table is proposed, and its validity is proved by computer simulations.
In order to select the optimal pulsars combination for X-ray Pulsar NAVigation (XPNAV), the influence factors of visibility, quality and space distribution of pulsars are studied. Besides, constraint equations for visibility based on the restrictions of celestial bodys shadow, X-ray disturbance source and detectors angle of view are built respectively; an evaluation equation for quality factor based on Cramer-Rao low bound is analyzed; the method for calculating Weighted Dilution Of Precision (WDOP), which decreases as the number of observable pulsars increases, is researched. Finally, a method for selecting pulsars based on looking up table is proposed, and its validity is proved by computer simulations.
2015, 37(10): 2363-2368.
doi: 10.11999/JEIT141480
Abstract:
In multiple platform electronic reconnaissance system, Time Difference Of Arrival (TDOA) of the pulse signal received by multiple stations can be used for signal sorting and positioning. However, when multiple emitter signals with similar parameters are mixed together in time and frequency domain, a lot of false TDOA information will be obtained by stations. Combined with Position Information Field (PIF) location method, a signal sorting and positioning method for similar radiation sources based on TDOA is proposed. TDOA information about similar radiation sources is firstly extracted from the pulses of all stations and TDOA window information by matching TDOA and multi-parameter in the proposed method. Then, multi-targets number and each targets position are obtained by position information field for target location method based on the TDOA information. Finally, positioning results are used to determine the real TDOA, eliminate the false TDOA, and complete signal sorting and target accurate positioning. Simulation results demonstrate the effectiveness and the practicality of this method.
In multiple platform electronic reconnaissance system, Time Difference Of Arrival (TDOA) of the pulse signal received by multiple stations can be used for signal sorting and positioning. However, when multiple emitter signals with similar parameters are mixed together in time and frequency domain, a lot of false TDOA information will be obtained by stations. Combined with Position Information Field (PIF) location method, a signal sorting and positioning method for similar radiation sources based on TDOA is proposed. TDOA information about similar radiation sources is firstly extracted from the pulses of all stations and TDOA window information by matching TDOA and multi-parameter in the proposed method. Then, multi-targets number and each targets position are obtained by position information field for target location method based on the TDOA information. Finally, positioning results are used to determine the real TDOA, eliminate the false TDOA, and complete signal sorting and target accurate positioning. Simulation results demonstrate the effectiveness and the practicality of this method.
2015, 37(10): 2369-2376.
doi: 10.11999/JEIT150013
Abstract:
The exiting algorithms for Angle Of Arrival (AOA) estimation of incident signal via phase interferometer may degrade significantly for near-field target. To deal with this issue, a Modified Steering Vector Matching (MSVM) algorithm with the good performance in both far field and near field is proposed. Symmetric array is employed to receive signal. The phase difference of antennas in symmetric position is independent on range as the terms related to range in arriving phases are cancelled. Accordingly, a cost function, which is only related to the AOA in near field, is derived, and the AOA of incident signal can be estimated by finding the maximal value of the cost function. Based on MSVM algorithm, an angle tracking loop is proposed by employing the feature that the gradient of cost function is proportional to the angle error. As a fast algorithm for finding local extremum of cost function, angle tracking loop is obviously more robust than other algorithm searching global maximum in terms of phase noise. Simulations are implemented to verify the excellent performance of angle tracking loop under different phase noise and range scenarios.
The exiting algorithms for Angle Of Arrival (AOA) estimation of incident signal via phase interferometer may degrade significantly for near-field target. To deal with this issue, a Modified Steering Vector Matching (MSVM) algorithm with the good performance in both far field and near field is proposed. Symmetric array is employed to receive signal. The phase difference of antennas in symmetric position is independent on range as the terms related to range in arriving phases are cancelled. Accordingly, a cost function, which is only related to the AOA in near field, is derived, and the AOA of incident signal can be estimated by finding the maximal value of the cost function. Based on MSVM algorithm, an angle tracking loop is proposed by employing the feature that the gradient of cost function is proportional to the angle error. As a fast algorithm for finding local extremum of cost function, angle tracking loop is obviously more robust than other algorithm searching global maximum in terms of phase noise. Simulations are implemented to verify the excellent performance of angle tracking loop under different phase noise and range scenarios.
2015, 37(10): 2377-2382.
doi: 10.11999/JEIT141590
Abstract:
Computational framework using surrogate functions and prior probability density functions, for smoothed L0 minimization approximation is studied in this paper, for the purpose of improving the recovery performance of non-convex compressed sensing. Firstly, a simple parameter adjusting strategy and modified SL0 and FOCUSS are presented, based on the convex-concave property analysis of approximation functions. Secondly, since L0 approximation problem can be viewed as a L0-Regularized Least Squares problem in noisy setting，a new computational framework called IRSL0 (Iteratively Reweighted SL0) is derived from the Newton direction, furthermore, a new surrogate function is also given. Finally, extensive numerical simulations demonstrate the robustness and applicability of the new theory and algorithms.
Computational framework using surrogate functions and prior probability density functions, for smoothed L0 minimization approximation is studied in this paper, for the purpose of improving the recovery performance of non-convex compressed sensing. Firstly, a simple parameter adjusting strategy and modified SL0 and FOCUSS are presented, based on the convex-concave property analysis of approximation functions. Secondly, since L0 approximation problem can be viewed as a L0-Regularized Least Squares problem in noisy setting，a new computational framework called IRSL0 (Iteratively Reweighted SL0) is derived from the Newton direction, furthermore, a new surrogate function is also given. Finally, extensive numerical simulations demonstrate the robustness and applicability of the new theory and algorithms.
2015, 37(10): 2383-2389.
doi: 10.11999/JEIT141632
Abstract:
Empirical Model Decomposition (EMD) and its improved algorithms are most useful signal processing methods. However, those methods still lack rigorous mathematical theory. This paper attempts to analyze mathematically the reconstruction errors for Ensemble EMD (EEMD) and EEMD with Adaptive Noises (EEMDAN). Moreover, the formulae of the residual noise are deduced step by step. There exists the residual noise in each intrinsic mode function during the EEMDAN. To suppress the residual noise, an improved ensemble empirical mode decomposition with complementary adaptive noises by adding pairs of positive and negative noises is proposed. The experimental results indicate that the proposed method can obviously reduce the residual noise in each intrinsic mode function compared with the EEMD and the EEMDAN, and it also has better signal reconstruction precision and faster signal decomposition.
Empirical Model Decomposition (EMD) and its improved algorithms are most useful signal processing methods. However, those methods still lack rigorous mathematical theory. This paper attempts to analyze mathematically the reconstruction errors for Ensemble EMD (EEMD) and EEMD with Adaptive Noises (EEMDAN). Moreover, the formulae of the residual noise are deduced step by step. There exists the residual noise in each intrinsic mode function during the EEMDAN. To suppress the residual noise, an improved ensemble empirical mode decomposition with complementary adaptive noises by adding pairs of positive and negative noises is proposed. The experimental results indicate that the proposed method can obviously reduce the residual noise in each intrinsic mode function compared with the EEMD and the EEMDAN, and it also has better signal reconstruction precision and faster signal decomposition.
2015, 37(10): 2390-2396.
doi: 10.11999/JEIT150112
Abstract:
Based on the idea that objects in a given image can be segmented by removing the background part, an unconstrained convex minimization problem is proposed. The penalization term added in the construction procedure of the proposed problem is proven to be viable, which is demonstrated by the experiment. At the computational level, a fixed-point operator and the corresponding algorithm are proposed by applying the theory of subdifferential and proximity operators, and Opial -averaged theorem. And then the convergence proof of the algorithm is given. Comparisons with other classical models show that the proposed segmentation model is more accurate. And the experiments also demonstrate that the fixed-point algorithm is faster than the gradient descent method and the split Bregman method. Moreover, the algorithm is robust to the initial curve and noise.
Based on the idea that objects in a given image can be segmented by removing the background part, an unconstrained convex minimization problem is proposed. The penalization term added in the construction procedure of the proposed problem is proven to be viable, which is demonstrated by the experiment. At the computational level, a fixed-point operator and the corresponding algorithm are proposed by applying the theory of subdifferential and proximity operators, and Opial -averaged theorem. And then the convergence proof of the algorithm is given. Comparisons with other classical models show that the proposed segmentation model is more accurate. And the experiments also demonstrate that the fixed-point algorithm is faster than the gradient descent method and the split Bregman method. Moreover, the algorithm is robust to the initial curve and noise.
2015, 37(10): 2397-2404.
doi: 10.11999/JEIT150183
Abstract:
In order to solve the problems of appearance change, local occlusion and background distraction in the visual tracking, a local patch tracking algorithm based on Fast Fourier Transform(FFT)is proposed. The tracking precision can be improved by establishing objects patch kernel ridge regression model and using patch exhaustive search based on circular structure matrix, and the efficiency can be improved by transforming time domains operation into frequency domains based on FFT. Firstly, patch kernel ridge regression model is constructed according to the initialized tracking area. Secondly, a patch exhaustive search method based on circular structure matrix is proposed, then the position model is constructed in adjoining frame. Finally, the position of the object is estimated accurately using the position model and the local patch model is updated. Experimental results indicate that the proposed algorithm not only can obtain a distinct improvement in coping with appearance change, local occlusion and background distraction, but also have high tracking efficiency.
In order to solve the problems of appearance change, local occlusion and background distraction in the visual tracking, a local patch tracking algorithm based on Fast Fourier Transform(FFT)is proposed. The tracking precision can be improved by establishing objects patch kernel ridge regression model and using patch exhaustive search based on circular structure matrix, and the efficiency can be improved by transforming time domains operation into frequency domains based on FFT. Firstly, patch kernel ridge regression model is constructed according to the initialized tracking area. Secondly, a patch exhaustive search method based on circular structure matrix is proposed, then the position model is constructed in adjoining frame. Finally, the position of the object is estimated accurately using the position model and the local patch model is updated. Experimental results indicate that the proposed algorithm not only can obtain a distinct improvement in coping with appearance change, local occlusion and background distraction, but also have high tracking efficiency.
2015, 37(10): 2405-2410.
doi: 10.11999/JEIT150278
Abstract:
Virtual network embedding is a critical issue in network virtualization. To overcome the ignorance of network local topology information in existing literatures, a Virtual Network Embedding (VNE) algorithm based on regional Resource Clustering Index (RCI-VNE), is proposed. In embedding preprocessing stage, a node regional resource clustering index evaluation algorithm is proposed, which considers local topology information and resource aggregation extent. In node embedding stage, a 2-adjacent aggregation node embedding algorithm based on the regional resource clustering index is also proposed. The algorithm embeds virtual nodes intensively to the location of abundant resources in substrate network and decreases embedding cost. Simulation results show that the algorithm improves virtual network request acceptance ratio, long-time average revenue and benefit-cost ratio compared with the existing embedding algorithms.
Virtual network embedding is a critical issue in network virtualization. To overcome the ignorance of network local topology information in existing literatures, a Virtual Network Embedding (VNE) algorithm based on regional Resource Clustering Index (RCI-VNE), is proposed. In embedding preprocessing stage, a node regional resource clustering index evaluation algorithm is proposed, which considers local topology information and resource aggregation extent. In node embedding stage, a 2-adjacent aggregation node embedding algorithm based on the regional resource clustering index is also proposed. The algorithm embeds virtual nodes intensively to the location of abundant resources in substrate network and decreases embedding cost. Simulation results show that the algorithm improves virtual network request acceptance ratio, long-time average revenue and benefit-cost ratio compared with the existing embedding algorithms.
2015, 37(10): 2411-2417.
doi: 10.11999/JEIT150231
Abstract:
Large-scale of wireless sensors are distributed to monitor smart grid equipment and user,s operating status information in smart grid. The original monitoring data are all collected to data processing center. And it brings huge data traffic pressure for communication network. Thus it is necessary to use data aggregation strategy in the process of data collection to reduce data traffic greatly, and reduce the overhead of communication network. This paper proposes asynchronous distributed aggregation layout construction algorithm based on hierarchical clustering. Firstly, a collection tree is constructed with the distance of all the nodes based on hierarchical clustering. Then the optimal numbers of clusters and group are calculated. And then, this paper selects the optimal aggregation nodes and constructs the best transmit topology with asynchronous distributed strategy. Finally, the simulation experiment shows that the algorithm could find the data aggregation mode of minimum cost quickly, and improve the efficiency for data collection in smart grid.
Large-scale of wireless sensors are distributed to monitor smart grid equipment and user,s operating status information in smart grid. The original monitoring data are all collected to data processing center. And it brings huge data traffic pressure for communication network. Thus it is necessary to use data aggregation strategy in the process of data collection to reduce data traffic greatly, and reduce the overhead of communication network. This paper proposes asynchronous distributed aggregation layout construction algorithm based on hierarchical clustering. Firstly, a collection tree is constructed with the distance of all the nodes based on hierarchical clustering. Then the optimal numbers of clusters and group are calculated. And then, this paper selects the optimal aggregation nodes and constructs the best transmit topology with asynchronous distributed strategy. Finally, the simulation experiment shows that the algorithm could find the data aggregation mode of minimum cost quickly, and improve the efficiency for data collection in smart grid.
2015, 37(10): 2418-2423.
doi: 10.11999/JEIT141205
Abstract:
For the problem of larger location error in Distance Vector-Hop (DV-Hop) localization algorithm, a genetic optimization DV-Hop localization algorithm based on error distance weighted and hop algorithm selection is proposed, namely WSGDV-Hop localization algorithm. The average every hop distance of anchor nodes is weighted by the error and the distance, the hop distance calculation method between unknown nodes to anchor nodes is selected by position judgment, and the calculated unknown nodes coordinates are optimized by improved genetic algorithm. The simulation results show that WSGDV-Hop localization algorithm achieves better performance than DV-Hop localization algorithm, the node location error is reduced, and the location accuracy is increased.
For the problem of larger location error in Distance Vector-Hop (DV-Hop) localization algorithm, a genetic optimization DV-Hop localization algorithm based on error distance weighted and hop algorithm selection is proposed, namely WSGDV-Hop localization algorithm. The average every hop distance of anchor nodes is weighted by the error and the distance, the hop distance calculation method between unknown nodes to anchor nodes is selected by position judgment, and the calculated unknown nodes coordinates are optimized by improved genetic algorithm. The simulation results show that WSGDV-Hop localization algorithm achieves better performance than DV-Hop localization algorithm, the node location error is reduced, and the location accuracy is increased.
2015, 37(10): 2424-2430.
doi: 10.11999/JEIT150111
Abstract:
In the Cognitive Radio Network (CRN) with multiple multi-antenna eavesdroppers, to make the system security rate maximum, secure communication over the physical layer that is subjected to the interference power constraints at the Primary Users (PU) is provided by designing the transmit covariance optimization of Secondary User Transmitter (SU-Tx).When?the?Channel State?Information (CSI) is known, the properties of the matrices and Charnes-Cooper transformation are used, the non-convex function is converted to a Semi-Definite Programming (SDP) to get the optimization scheme of SU-Tx. Simulation results show that compared with the existing sub-optimal transmission designs, the proposed method improves the secrecy rate and has more advantages on the complexity.
In the Cognitive Radio Network (CRN) with multiple multi-antenna eavesdroppers, to make the system security rate maximum, secure communication over the physical layer that is subjected to the interference power constraints at the Primary Users (PU) is provided by designing the transmit covariance optimization of Secondary User Transmitter (SU-Tx).When?the?Channel State?Information (CSI) is known, the properties of the matrices and Charnes-Cooper transformation are used, the non-convex function is converted to a Semi-Definite Programming (SDP) to get the optimization scheme of SU-Tx. Simulation results show that compared with the existing sub-optimal transmission designs, the proposed method improves the secrecy rate and has more advantages on the complexity.
2015, 37(10): 2431-2437.
doi: 10.11999/JEIT150285
Abstract:
WiFi network helps offload the traffic pressure in cellular networks and alleviate its traffic congestion. However, it can merely offload the traffic within its coverage. In view of the mobility of users, if the users beyond WiFi coverage are incentivized with certain rewards to postpone their present cellular network services, and wait till they enter WiFi coverage, the traffic offloading capacity of WiFi Network will be significantly enhanced. This paper discusses an incentive mechanism for the operator to encourage users to delay their cellular network services and switch to WiFi network, and formulates the problem as a two-stage Stackelberg game. In this game, an operator expects to adopt an optimum reward solution, giving considerations to the extent of cellular network congestion and the required reward for users. Optimal reward mechanisms for the operators are proposed. According to the research result, the proposed incentive mechanism can effectively reduce the total costs of operators including the cellular network congestion costs and the user reward costs.
WiFi network helps offload the traffic pressure in cellular networks and alleviate its traffic congestion. However, it can merely offload the traffic within its coverage. In view of the mobility of users, if the users beyond WiFi coverage are incentivized with certain rewards to postpone their present cellular network services, and wait till they enter WiFi coverage, the traffic offloading capacity of WiFi Network will be significantly enhanced. This paper discusses an incentive mechanism for the operator to encourage users to delay their cellular network services and switch to WiFi network, and formulates the problem as a two-stage Stackelberg game. In this game, an operator expects to adopt an optimum reward solution, giving considerations to the extent of cellular network congestion and the required reward for users. Optimal reward mechanisms for the operators are proposed. According to the research result, the proposed incentive mechanism can effectively reduce the total costs of operators including the cellular network congestion costs and the user reward costs.
2015, 37(10): 2438-2445.
doi: 10.11999/JEIT150044
Abstract:
A dynamic channel allocation algorithm is proposed to avoid all interference and improve spectrum efficiency in Multimedia Broadcast multicast service Single Frequency Networks (MBSFN). Four electromagnetic compatibility constraint functions are redefined according to the topology information of MBSFN. In order to avoid all intra-area and inter-area interference of MBSFN, a novel energy function of Noise-tuning-based Hysteretic Noisy Chaotic Neural Network (NHNCNN) is constructed elaborately based on renewed constraint functions. Also, the judgment process of the stable state of NHNCNN is developed to accelerate system convergence. Specifically, the dichotomy method is adopted jointly to minimize the total number of allocated channels so as to further improve spectrum efficiency. Simulation results show that a feasible solution without any interference can be effectively searched by the improved NHNCNN. Finally, the optimal solution with minimum total channel number is found. Compared with existing algorithms, the proposed algorithm achieves better convergence speed and quality of solution.
A dynamic channel allocation algorithm is proposed to avoid all interference and improve spectrum efficiency in Multimedia Broadcast multicast service Single Frequency Networks (MBSFN). Four electromagnetic compatibility constraint functions are redefined according to the topology information of MBSFN. In order to avoid all intra-area and inter-area interference of MBSFN, a novel energy function of Noise-tuning-based Hysteretic Noisy Chaotic Neural Network (NHNCNN) is constructed elaborately based on renewed constraint functions. Also, the judgment process of the stable state of NHNCNN is developed to accelerate system convergence. Specifically, the dichotomy method is adopted jointly to minimize the total number of allocated channels so as to further improve spectrum efficiency. Simulation results show that a feasible solution without any interference can be effectively searched by the improved NHNCNN. Finally, the optimal solution with minimum total channel number is found. Compared with existing algorithms, the proposed algorithm achieves better convergence speed and quality of solution.
2015, 37(10): 2446-2451.
doi: 10.11999/JEIT141444
Abstract:
There is often no cellular connection in the basement level of large buildings and in remote unpopulated areas. In this paper, a relay is deployed to extend the wireless coverage of a base station to a target area. Models, analytical results, and algorithms are proposed to study the optimal relay position and power allocation for minimizing the maximum outage probability over the entire area. Based on the analysis, as the total transmit power of the base station and relay increases, the optimal relay position and the transmit power ratio of the base station and relay remain the same. The complexity of the proposed algorithm is much lower than, but it achieves almost the same performance as that of the exhaustive searching method based on numerical simulations, which is more suitable for the practical system.
There is often no cellular connection in the basement level of large buildings and in remote unpopulated areas. In this paper, a relay is deployed to extend the wireless coverage of a base station to a target area. Models, analytical results, and algorithms are proposed to study the optimal relay position and power allocation for minimizing the maximum outage probability over the entire area. Based on the analysis, as the total transmit power of the base station and relay increases, the optimal relay position and the transmit power ratio of the base station and relay remain the same. The complexity of the proposed algorithm is much lower than, but it achieves almost the same performance as that of the exhaustive searching method based on numerical simulations, which is more suitable for the practical system.
2015, 37(10): 2452-2459.
doi: 10.11999/JEIT150004
Abstract:
In order to improve the efficiency and the reliability of the helicopter guiding in the beacon researching and locate landing, an encoding communication scheme based on unequal level coding Luby Transform (LT) code is proposed. Different communication strategies are proposed for different scenarios. The different guiding strategies considering the unequal level coding scheme are designed. The bit error rate of the unequal level coding LT code with different communication strategies is analyzed. The coding scheme and communication strategy are simulated by computer. The simulation results show that the bit error rate of the unequal level protection encoding scheme is significantly reduced and the coding performance is improved over binary erasure channel. The strategies can adapt to different channel environments, and the reliability of communication is improved. Thus, helicopter emergency landing safety is improved.
In order to improve the efficiency and the reliability of the helicopter guiding in the beacon researching and locate landing, an encoding communication scheme based on unequal level coding Luby Transform (LT) code is proposed. Different communication strategies are proposed for different scenarios. The different guiding strategies considering the unequal level coding scheme are designed. The bit error rate of the unequal level coding LT code with different communication strategies is analyzed. The coding scheme and communication strategy are simulated by computer. The simulation results show that the bit error rate of the unequal level protection encoding scheme is significantly reduced and the coding performance is improved over binary erasure channel. The strategies can adapt to different channel environments, and the reliability of communication is improved. Thus, helicopter emergency landing safety is improved.
2015, 37(10): 2460-2465.
doi: 10.11999/JEIT150168
Abstract:
The Maximum Hamming Correlation (MHC) and the Average Hamming Correlation (AHC) are two important performance measures of the frequency-hopping sequences. Firstly, some properties of generalized cyclotomy are derived from Fermat quotient. Secondly, based on the generalized cyclotomy, a class of optimal frequency-hopping sequences set with length of sequences p2 and size beingp defined on Zp is constructed. Finally, it is proved that the proposed frequency-hopping sequences set is optimal with respect to the maximum Hamming correlation bound and the average Hamming correlation bound.
The Maximum Hamming Correlation (MHC) and the Average Hamming Correlation (AHC) are two important performance measures of the frequency-hopping sequences. Firstly, some properties of generalized cyclotomy are derived from Fermat quotient. Secondly, based on the generalized cyclotomy, a class of optimal frequency-hopping sequences set with length of sequences p2 and size beingp defined on Zp is constructed. Finally, it is proved that the proposed frequency-hopping sequences set is optimal with respect to the maximum Hamming correlation bound and the average Hamming correlation bound.
2015, 37(10): 2466-2474.
doi: 10.11999/JEIT150144
Abstract:
Research on the relay-satellite scheduling problem provides scientific decision-making methods for the task planning of the Tracking and Data Relay Satellite Systems (TDRSS). How to develop a reasonable scheduling model and design the scheduling algorithm according to the model are two key issues to address. In this paper, according to the characteristics of the relay satellite scheduling problem, incorporating the constraints brought by the visible time window between the relay satellite and the user spacecraft, mission attributes submitted by users, and the limited resources of the relay satellite, a scheduling programming model is established. Furthermore, a scheduling algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed. Finally, the simulation data analysis shows that the scheduling algorithm based on the ABC algorithm is an effective and reasonable scheduling method.
Research on the relay-satellite scheduling problem provides scientific decision-making methods for the task planning of the Tracking and Data Relay Satellite Systems (TDRSS). How to develop a reasonable scheduling model and design the scheduling algorithm according to the model are two key issues to address. In this paper, according to the characteristics of the relay satellite scheduling problem, incorporating the constraints brought by the visible time window between the relay satellite and the user spacecraft, mission attributes submitted by users, and the limited resources of the relay satellite, a scheduling programming model is established. Furthermore, a scheduling algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed. Finally, the simulation data analysis shows that the scheduling algorithm based on the ABC algorithm is an effective and reasonable scheduling method.
2015, 37(10): 2475-2482.
doi: 10.11999/JEIT150472
Abstract:
Most existing rain attenuation prediction models are only tested at 55 GHz. There are small numbers of tested W-band rain attenuation prediction models, but these tested models have issues with high complexity and large quantities of calculations. A real-time prediction method is proposed that has a simpler structure and smaller quantity of calculations. The proposed method is based on the ARIMA model, which utilizes the relationship among the time series to establish a prediction model, conducts a stationary test on the original time series, transforms the nonstationary time series into a stationary time series by using a difference transform, and estimates the parameters of the stationary time series. This sequentially transforms the traditional nonlinear prediction into a linear prediction. First, the ARIMA (1,1,6) model is compared under the conditions of different polarizations, prediction intervals, and numbers of time series. Then the proposed model is compared with the International Telecommunication Union-R (ITU-R) and the Silva Mello rain attenuation prediction models using the conditions of vertical polarization, a prediction interval of 0.10 GHz, and a number of 50 time series. Finally, the forecasting time series with the simulant series are compared. The result shows that the prediction error between the ARIMA model, the ITU-R model and the Silva Mello model does not exceed10-3, and that the change trend of the rain attenuation is basically the same. and the goodness of fit between the forecasting and simulant time series is good, which means that the proposed model can be applied to forecasting the rain attenuation in the W band, and that it has the advantages of simpler structure and high precision in prediction.
Most existing rain attenuation prediction models are only tested at 55 GHz. There are small numbers of tested W-band rain attenuation prediction models, but these tested models have issues with high complexity and large quantities of calculations. A real-time prediction method is proposed that has a simpler structure and smaller quantity of calculations. The proposed method is based on the ARIMA model, which utilizes the relationship among the time series to establish a prediction model, conducts a stationary test on the original time series, transforms the nonstationary time series into a stationary time series by using a difference transform, and estimates the parameters of the stationary time series. This sequentially transforms the traditional nonlinear prediction into a linear prediction. First, the ARIMA (1,1,6) model is compared under the conditions of different polarizations, prediction intervals, and numbers of time series. Then the proposed model is compared with the International Telecommunication Union-R (ITU-R) and the Silva Mello rain attenuation prediction models using the conditions of vertical polarization, a prediction interval of 0.10 GHz, and a number of 50 time series. Finally, the forecasting time series with the simulant series are compared. The result shows that the prediction error between the ARIMA model, the ITU-R model and the Silva Mello model does not exceed10-3, and that the change trend of the rain attenuation is basically the same. and the goodness of fit between the forecasting and simulant time series is good, which means that the proposed model can be applied to forecasting the rain attenuation in the W band, and that it has the advantages of simpler structure and high precision in prediction.
2015, 37(10): 2483-2489.
doi: 10.11999/JEIT150030
Abstract:
In order to eliminate the Multiple Access Interference (MAI) and Multipath Interference (MI), and avoid inter-cell interference from adjacent cells in Quasi-Synchronous Code Division Multiple Access (QS-CDMA) system, one class of asymmetric sequences pairs with Zero-Correlation Zone (ZCZ) are proposed. Based on the interleaved technique, a new Asymmetric-ZCZ (A-ZCZ) sequence pair set can be generated from a given perfect auto-correlation sequence pair. The presented A-ZCZ sequence pairs contains of multiple subsets which are the traditional ZCZ sequence pairs. The Cross-Correlation Function (CCF) between any two sequence pairs of different subsets has a wider Zero-Cross-Correlation Zone (ZCCZ). As a benefit, the ZCZ length of A-ZCZ sequence pair set can be flexibly chosen according to the requirement of the system.
In order to eliminate the Multiple Access Interference (MAI) and Multipath Interference (MI), and avoid inter-cell interference from adjacent cells in Quasi-Synchronous Code Division Multiple Access (QS-CDMA) system, one class of asymmetric sequences pairs with Zero-Correlation Zone (ZCZ) are proposed. Based on the interleaved technique, a new Asymmetric-ZCZ (A-ZCZ) sequence pair set can be generated from a given perfect auto-correlation sequence pair. The presented A-ZCZ sequence pairs contains of multiple subsets which are the traditional ZCZ sequence pairs. The Cross-Correlation Function (CCF) between any two sequence pairs of different subsets has a wider Zero-Cross-Correlation Zone (ZCCZ). As a benefit, the ZCZ length of A-ZCZ sequence pair set can be flexibly chosen according to the requirement of the system.
2015, 37(10): 2490-2494.
doi: 10.11999/JEIT150180
Abstract:
Based on the theory of generalized cyclotomic, a new class of binaey generalized cyclotomic sequences of order four with period2p2 is established. Using the theory of polynomial factor over finite field, the linear complexity and minimal polynomial of the new sequences are researched. Results show that the sequences has larger linear complexity and can resist the attack by B-M algorithm. It is a good sequence from the viewpoint of cryptography.
Based on the theory of generalized cyclotomic, a new class of binaey generalized cyclotomic sequences of order four with period2p2 is established. Using the theory of polynomial factor over finite field, the linear complexity and minimal polynomial of the new sequences are researched. Results show that the sequences has larger linear complexity and can resist the attack by B-M algorithm. It is a good sequence from the viewpoint of cryptography.
2015, 37(10): 2495-2500.
doi: 10.11999/JEIT150067
Abstract:
To slove the problems that Chinese Remainder Theorem (CRT) based threshold RSA signature scheme can not be used to sign some messages and the amount of computation in partial signatures combining phase is large, an improving method is proposed, in which a virtual group member is introduced, making the scheme can be used to sign all messages and significantly reducing the amount of computation in partial signatures combining phase, e.g. when the threshold value is 10, the amount of computation in partial signatures combining phase can be reduced to 1/6 of the original. The security and practicability of the improved scheme are analyzed. Results show that it is non-forgeable against an adaptive chosen message attack and more efficient than other threshold RSA signatures.
To slove the problems that Chinese Remainder Theorem (CRT) based threshold RSA signature scheme can not be used to sign some messages and the amount of computation in partial signatures combining phase is large, an improving method is proposed, in which a virtual group member is introduced, making the scheme can be used to sign all messages and significantly reducing the amount of computation in partial signatures combining phase, e.g. when the threshold value is 10, the amount of computation in partial signatures combining phase can be reduced to 1/6 of the original. The security and practicability of the improved scheme are analyzed. Results show that it is non-forgeable against an adaptive chosen message attack and more efficient than other threshold RSA signatures.
2015, 37(10): 2501-2507.
doi: 10.11999/JEIT150291
Abstract:
Using genetic algorithms to generate test data automatically is becoming a hot topic in recent years, the method on effectively generating data is highly dependent on choosing the proper fitness function and the selecting standard. The genetic algorithm is used on Integrated Management X-software (IMX) system to help it improve the quality of regression test. Those basic test data used in this paper are taken from the data that generated by professional testers in IMX, and an initial population selecting standard is proposed based on the coverage. Experiments on IMX and triangle program show that the proposed algorithm is more effective than others, for example, with less time and iteration the method can find the testing data correctly, especially on data variety.
Using genetic algorithms to generate test data automatically is becoming a hot topic in recent years, the method on effectively generating data is highly dependent on choosing the proper fitness function and the selecting standard. The genetic algorithm is used on Integrated Management X-software (IMX) system to help it improve the quality of regression test. Those basic test data used in this paper are taken from the data that generated by professional testers in IMX, and an initial population selecting standard is proposed based on the coverage. Experiments on IMX and triangle program show that the proposed algorithm is more effective than others, for example, with less time and iteration the method can find the testing data correctly, especially on data variety.
2015, 37(10): 2508-2516.
doi: 10.11999/JEIT150130
Abstract:
With the widely spread of virtualization technology, the security problems of virtual layer have attracted the close attention of domestic and foreign researchers at the same time. Existing virtual machine monitor (or Hypervisor) integrity protection methods mainly focus on code and control data integrity protection, and can not resist the non-control data attacks; using periodic monitoring can not provide real-time non-control data integrity protection. According to the deficiencies of the existing methods, Hypervisor non-control data integrity protection model UCONhi is proposed based on Usage CONtral (UCON). The model simplifies the UCON model according to the needs of the non-control data integrity protection, inheriting the continuity and mutability of UCON model to realize real-time access control of non-control data. The attacker and the attacked object are analyzed to determine the subjects and objects and reduce the security policies according to the attacking samples, and UCONhi security policies are described based on ECA, which can effectively decide the legality of non-control data access. A prototype system Xen-UCONhi is designed and implemented based on Xen system, and the effectiveness and performance overhead of Xen-UCONhi are evaluated by comprehensive experiments. The results show that Xen-UCONhi can effectively prevent attacks against Hypervisor with less than 10% performance overhead.
With the widely spread of virtualization technology, the security problems of virtual layer have attracted the close attention of domestic and foreign researchers at the same time. Existing virtual machine monitor (or Hypervisor) integrity protection methods mainly focus on code and control data integrity protection, and can not resist the non-control data attacks; using periodic monitoring can not provide real-time non-control data integrity protection. According to the deficiencies of the existing methods, Hypervisor non-control data integrity protection model UCONhi is proposed based on Usage CONtral (UCON). The model simplifies the UCON model according to the needs of the non-control data integrity protection, inheriting the continuity and mutability of UCON model to realize real-time access control of non-control data. The attacker and the attacked object are analyzed to determine the subjects and objects and reduce the security policies according to the attacking samples, and UCONhi security policies are described based on ECA, which can effectively decide the legality of non-control data access. A prototype system Xen-UCONhi is designed and implemented based on Xen system, and the effectiveness and performance overhead of Xen-UCONhi are evaluated by comprehensive experiments. The results show that Xen-UCONhi can effectively prevent attacks against Hypervisor with less than 10% performance overhead.
2015, 37(10): 2517-2520.
doi: 10.11999/JEIT150038
Abstract:
This paper presents a new 44 millimeter-wave antenna array, which adopts the magneto-electric dipole as the radiating element and a type of coplanar waveguide feed network to excite the array. This design not only provides very wide impedance and gain bandwidths, but also has features of low cost and ease in fabrication. The simulated and measured results reveal that this array exhibits a wide impedance bandwidth of 54.5% and a wide 3 dB gain bandwidth of 37.1%. Over the operating frequency band (40.2~70.0 GHz), the maximum gain is 18.1 dBi. However, other 44 millimeter-wave antenna arrays, designed based on microstrip patch antenna or electric dipole antenna, have the operating bandwidth of about 20% and the gain of 16~17 dBi. Hence, the proposed antenna has an obvious advantage. In addition, the simulated and measured results have a good agreement.
This paper presents a new 44 millimeter-wave antenna array, which adopts the magneto-electric dipole as the radiating element and a type of coplanar waveguide feed network to excite the array. This design not only provides very wide impedance and gain bandwidths, but also has features of low cost and ease in fabrication. The simulated and measured results reveal that this array exhibits a wide impedance bandwidth of 54.5% and a wide 3 dB gain bandwidth of 37.1%. Over the operating frequency band (40.2~70.0 GHz), the maximum gain is 18.1 dBi. However, other 44 millimeter-wave antenna arrays, designed based on microstrip patch antenna or electric dipole antenna, have the operating bandwidth of about 20% and the gain of 16~17 dBi. Hence, the proposed antenna has an obvious advantage. In addition, the simulated and measured results have a good agreement.
2015, 37(10): 2521-2528.
doi: 10.11999/JEIT150162
Abstract:
A circuit characteristics-driven semi-supervised modelling approach is proposed for FPGA architecture design space exploration. By including circuit characteristics as input, the proposed approach can estimate the performance of specific circuit on certain architecture accurately. Experimental results illustrate that the approach estimates the area with Mean Relative Error (MRE) up to 6.25%, and delay up to 4.23%, which is comparable to the Semi-supervised Model Tree (SMT) approach. Meanwhile, the proposed approach speedups the modelling process. Compared to the SMT approach, the proposed approach reduces the time cost from 500 h to 250 h when exploring a design space with millions of architectures inside on Intel Xeon E7-4807 platform.
A circuit characteristics-driven semi-supervised modelling approach is proposed for FPGA architecture design space exploration. By including circuit characteristics as input, the proposed approach can estimate the performance of specific circuit on certain architecture accurately. Experimental results illustrate that the approach estimates the area with Mean Relative Error (MRE) up to 6.25%, and delay up to 4.23%, which is comparable to the Semi-supervised Model Tree (SMT) approach. Meanwhile, the proposed approach speedups the modelling process. Compared to the SMT approach, the proposed approach reduces the time cost from 500 h to 250 h when exploring a design space with millions of architectures inside on Intel Xeon E7-4807 platform.
2015, 37(10): 2529-2535.
doi: 10.11999/JEIT150177
Abstract:
An adaptive Extended Frequency-Directed Run-length (EFDR) code method for test data compression is presented in this paper. The method is based on EFDR code, and adds an additional parameter N, which is used to represent the code length difference between tail and prefix. According to the distribution of the runs in each test vector of the test set, the method selects the most suitable N values to code, and it can improve the compression ratio. For the decompression, according to the size of the codeword, the run length of the original test data can be obtained with a simple mathematical operation. Meanwhile, those codeword under different parameter values can be decoded by the same decompression circuit. Thus, the decompression circuit can keep in a low hardware cost level. The experimental result shows that the average compression rate of the proposed method can achieve to 69.87%, over 4.07% than original EFDR code method.
An adaptive Extended Frequency-Directed Run-length (EFDR) code method for test data compression is presented in this paper. The method is based on EFDR code, and adds an additional parameter N, which is used to represent the code length difference between tail and prefix. According to the distribution of the runs in each test vector of the test set, the method selects the most suitable N values to code, and it can improve the compression ratio. For the decompression, according to the size of the codeword, the run length of the original test data can be obtained with a simple mathematical operation. Meanwhile, those codeword under different parameter values can be decoded by the same decompression circuit. Thus, the decompression circuit can keep in a low hardware cost level. The experimental result shows that the average compression rate of the proposed method can achieve to 69.87%, over 4.07% than original EFDR code method.
2015, 37(10): 2536-2540.
doi: 10.11999/JEIT150148
Abstract:
MultiSite Radar Systems (MSRS) can significantly improve target localization performance. However, due to the difference of signal-to-noise ratios of separate radar sites, there usually exist some radar sites that have not initiated a target track, hence target localization accuracy can not be improved to the best. So an interesting problem is how to use target tracking information provided by other radar sites to improve the detection performance of the radar sites that have not initiated the target track. In this paper, a track initiation algorithm based on tracking information is proposed. Firstly, the target tracking information provided by the radar sites that have already tracked a target is transmitted to the radar sites that have not initiated the target track. Then, a predicted gate is established according to the tracking information and target dynamic model. Finally detection thresholds in the predicted gate are adjusted under a constant probability of false track initiation, and target detection and track initiation are accomplished. Numerical results indicate that the proposed algorithm can significantly improve the probability of target detection and target track initiation.
MultiSite Radar Systems (MSRS) can significantly improve target localization performance. However, due to the difference of signal-to-noise ratios of separate radar sites, there usually exist some radar sites that have not initiated a target track, hence target localization accuracy can not be improved to the best. So an interesting problem is how to use target tracking information provided by other radar sites to improve the detection performance of the radar sites that have not initiated the target track. In this paper, a track initiation algorithm based on tracking information is proposed. Firstly, the target tracking information provided by the radar sites that have already tracked a target is transmitted to the radar sites that have not initiated the target track. Then, a predicted gate is established according to the tracking information and target dynamic model. Finally detection thresholds in the predicted gate are adjusted under a constant probability of false track initiation, and target detection and track initiation are accomplished. Numerical results indicate that the proposed algorithm can significantly improve the probability of target detection and target track initiation.
