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2014 Vol. 36, No. 3
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2014, 36(3): 509-515.
doi: 10.3724/SP.J.1146.2013.00656
Abstract:
Almost all the existing works on power allocation assume that the target Radar Cross Section (RCS) information is known a priori. In order to deal with the uncertainty of the target RCS, a robust power allocation algorithm for MultiStatic Radar Systems (MSRS) is proposed based on Nonlinear Chance Constrained Programming (NCCP), in which the target RCS is modeled as a random variable with unknown distribution. Firstly, the Bayesian Cramer Rao Lower Bound (BCRLB) is derived. Then, the NCCP model is built with the objective of minimizing the total transmit power of MSRS, while the BCRLB outage probability is enforced to be greater than a specified probability. The resulting stochastic optimization issue is solved via Conditional Value at Risk (CVaR) relaxation and Sample Average Approximation (SAA) method. Finally, the validity and robustness of the proposed algorithm are verified with the simulation results.
Almost all the existing works on power allocation assume that the target Radar Cross Section (RCS) information is known a priori. In order to deal with the uncertainty of the target RCS, a robust power allocation algorithm for MultiStatic Radar Systems (MSRS) is proposed based on Nonlinear Chance Constrained Programming (NCCP), in which the target RCS is modeled as a random variable with unknown distribution. Firstly, the Bayesian Cramer Rao Lower Bound (BCRLB) is derived. Then, the NCCP model is built with the objective of minimizing the total transmit power of MSRS, while the BCRLB outage probability is enforced to be greater than a specified probability. The resulting stochastic optimization issue is solved via Conditional Value at Risk (CVaR) relaxation and Sample Average Approximation (SAA) method. Finally, the validity and robustness of the proposed algorithm are verified with the simulation results.
2014, 36(3): 516-522.
doi: 10.3724/SP.J.1146.2013.00108
Abstract:
It is necessary to take mutual coupling of arrays into account in the research of array pattern synthesis for Opportunistic Array Radar (OAR) with a large number of antenna elements randomly distributed in the space. Active element patterns of a large array are constructed from those of a small array. In this paper, based on the idea of the sub-array, the large array is divided into across some sub-arrays, which can include the same elements. Building the mutual impedance matrix?of?large arbitrary array with the mutual impedance matrix?of the sub-array and combining with adaptive algorithm to realize the beam pattern synthesis optimization for OAR. The method of moment is used to calculate the generalized mutual impedance matrix of sub-arrays in this method. Last, based on maxim output signal-to-noise rate criteria, adding imaginary jammers into angle domain to adaptively change weights of the array factors for synthesizing patterns. An uniform linear array and a plane array are synthesized with the method. Calculated results agree with that with FEKO Software Simulation.
It is necessary to take mutual coupling of arrays into account in the research of array pattern synthesis for Opportunistic Array Radar (OAR) with a large number of antenna elements randomly distributed in the space. Active element patterns of a large array are constructed from those of a small array. In this paper, based on the idea of the sub-array, the large array is divided into across some sub-arrays, which can include the same elements. Building the mutual impedance matrix?of?large arbitrary array with the mutual impedance matrix?of the sub-array and combining with adaptive algorithm to realize the beam pattern synthesis optimization for OAR. The method of moment is used to calculate the generalized mutual impedance matrix of sub-arrays in this method. Last, based on maxim output signal-to-noise rate criteria, adding imaginary jammers into angle domain to adaptively change weights of the array factors for synthesizing patterns. An uniform linear array and a plane array are synthesized with the method. Calculated results agree with that with FEKO Software Simulation.
2014, 36(3): 523-528.
doi: 10.3724/SP.J.1146.2013.00365
Abstract:
For a model derived from the Geometrical Theory of Diffraction (GTD), a fast method based on spatial filtering is proposed to extract parameters of two-dimensional scattering centers. The proposed method utilizes spatial filtering process to decompose two-dimensional scattering centers extraction into several times of one-dimensional scattering centers extraction, in which the one-dimensional Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) is employed to estimate the parameters of scattering centers for each dimensional independently. Finally, the pair-matching of two-dimensional parameters is accomplished by searching the minimums of Euclidean distance. Compared with the method based on two-dimensional ESPRIT, the proposed method does not need high-dimensional eigenvalue decomposition, thus the computational complexity is significantly reduced. Simulation results show that the proposed method not only reduces greatly the computational burden, but also keeps high accuracy of parameter estimation compared with 2D-ESPRIT algorithm, and it is proved to be effective in scattering center extraction.
For a model derived from the Geometrical Theory of Diffraction (GTD), a fast method based on spatial filtering is proposed to extract parameters of two-dimensional scattering centers. The proposed method utilizes spatial filtering process to decompose two-dimensional scattering centers extraction into several times of one-dimensional scattering centers extraction, in which the one-dimensional Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) is employed to estimate the parameters of scattering centers for each dimensional independently. Finally, the pair-matching of two-dimensional parameters is accomplished by searching the minimums of Euclidean distance. Compared with the method based on two-dimensional ESPRIT, the proposed method does not need high-dimensional eigenvalue decomposition, thus the computational complexity is significantly reduced. Simulation results show that the proposed method not only reduces greatly the computational burden, but also keeps high accuracy of parameter estimation compared with 2D-ESPRIT algorithm, and it is proved to be effective in scattering center extraction.
2014, 36(3): 529-536.
doi: 10.3724/SP.J.1146.2013.00616
Abstract:
Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). Because of the complicate electromagnetic scattering in real target and background clutter, the traditional method based on the template of average HRRP does not has a good performance sometimes. The geometric structure of HRRPs on the unit hypersphere is analyzed, and the templates of cluster center and affinity sphere are built. Based on the affinity sphere, the new distance measure is defined. Finally a new recognition method is proposed based on the affinity among HRRPs. The experiment results based on MSTAR data demonstrate that the proposed method achieves a good engineering performance.
Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). Because of the complicate electromagnetic scattering in real target and background clutter, the traditional method based on the template of average HRRP does not has a good performance sometimes. The geometric structure of HRRPs on the unit hypersphere is analyzed, and the templates of cluster center and affinity sphere are built. Based on the affinity sphere, the new distance measure is defined. Finally a new recognition method is proposed based on the affinity among HRRPs. The experiment results based on MSTAR data demonstrate that the proposed method achieves a good engineering performance.
2014, 36(3): 537-544.
doi: 10.3724/SP.J.1146.2013.00613
Abstract:
The redundant calculation in Back-Projection Algorithm (BPA) is studied in Fast Factorized BPA (FFBPA). By dividing sub-apertures and accumulating signal coherently in polar format coordinate, image with high resolution is obtained. The progress of repeatedly searching every signal in full aperture for every pixel is avoided in FFBPA, thus the amount of computation is reduced. However, multi-stage interpolation operation increases the error accumulation. Combining with the original Polar Format Algorithm (PFA), a new multi-stage iteration Fast PFA is proposed, and it is modified to process data in curve orbit and multiple modes SAR. Analysis indicates that the proposed algorithm is more efficient than FFBPA in practice. Comparison of simulation results of spaceborne spotlight SAR with very high resolution (0.1 m) processed by the proposed algorithm and FFBPA verifies the superiority of the new algorithm over FFBPA.
The redundant calculation in Back-Projection Algorithm (BPA) is studied in Fast Factorized BPA (FFBPA). By dividing sub-apertures and accumulating signal coherently in polar format coordinate, image with high resolution is obtained. The progress of repeatedly searching every signal in full aperture for every pixel is avoided in FFBPA, thus the amount of computation is reduced. However, multi-stage interpolation operation increases the error accumulation. Combining with the original Polar Format Algorithm (PFA), a new multi-stage iteration Fast PFA is proposed, and it is modified to process data in curve orbit and multiple modes SAR. Analysis indicates that the proposed algorithm is more efficient than FFBPA in practice. Comparison of simulation results of spaceborne spotlight SAR with very high resolution (0.1 m) processed by the proposed algorithm and FFBPA verifies the superiority of the new algorithm over FFBPA.
2014, 36(3): 545-551.
doi: 10.3724/SP.J.1146.2013.00579
Abstract:
Image quality of azimuth multi-channel SAR is influenced by such factors as system parameters, array errors, and signal processing strategies. The image quality of azimuth multi-channel SAR is studied deeply. Firstly, the signal model is improved. The introduction of the reconstruction coefficient provides more flexibility for designing the reconstruction network. In the frame of digital beam-forming, a series of reconstruction algorithms are then discussed for signal reconstruction. Secondly, based on the power spectrum of the reconstruction error, the analytical expressions of output Signal to Noise Ratio (SNR) and Azimuth Ambiguity to Signal Ratio (AASR) are deduced. Thirdly, the performance of the reconstruction algorithms is assessed quantitatively. Simulation experiment results confirm the validity of the theoretical analysis. Theoretical results provide technique support to system design, signal processing and image quality evaluation of azimuth multi-channel SAR.
Image quality of azimuth multi-channel SAR is influenced by such factors as system parameters, array errors, and signal processing strategies. The image quality of azimuth multi-channel SAR is studied deeply. Firstly, the signal model is improved. The introduction of the reconstruction coefficient provides more flexibility for designing the reconstruction network. In the frame of digital beam-forming, a series of reconstruction algorithms are then discussed for signal reconstruction. Secondly, based on the power spectrum of the reconstruction error, the analytical expressions of output Signal to Noise Ratio (SNR) and Azimuth Ambiguity to Signal Ratio (AASR) are deduced. Thirdly, the performance of the reconstruction algorithms is assessed quantitatively. Simulation experiment results confirm the validity of the theoretical analysis. Theoretical results provide technique support to system design, signal processing and image quality evaluation of azimuth multi-channel SAR.
2014, 36(3): 552-558.
doi: 10.3724/SP.J.1146.2013.00676
Abstract:
To deal with the issue that the long time accumulation method is hard to be applied to the detection and parameter estimation of Linear Frequency Modulated Continuous Wave (LFMCW) signal, a novel algorithm combining the joint inter-frame correlation method and cyclostationary method is proposed to detect LFMCW signal and estimate its parameters. Firstly, consistency of noise variance is completed by the normalized window-variant coherent average method. Then, on this basis, the period is exactly estimated with inter-frame correlation method. Finally, cyclostationary method is utilized to estimate the phase parameters of LFMCW signal. The proposed algorithm realizes long time accumulation with low computational complexity. For low Signal- to-Noise Ratio (SNR), this method still achieves good estimation performance. Simulation results verify the effectiveness of the proposed method.
To deal with the issue that the long time accumulation method is hard to be applied to the detection and parameter estimation of Linear Frequency Modulated Continuous Wave (LFMCW) signal, a novel algorithm combining the joint inter-frame correlation method and cyclostationary method is proposed to detect LFMCW signal and estimate its parameters. Firstly, consistency of noise variance is completed by the normalized window-variant coherent average method. Then, on this basis, the period is exactly estimated with inter-frame correlation method. Finally, cyclostationary method is utilized to estimate the phase parameters of LFMCW signal. The proposed algorithm realizes long time accumulation with low computational complexity. For low Signal- to-Noise Ratio (SNR), this method still achieves good estimation performance. Simulation results verify the effectiveness of the proposed method.
2014, 36(3): 559-564.
doi: 10.3724/SP.J.1146.2013.00829
Abstract:
Costas-coded Frequency Hopping (FH) signal is very sensitive to velocity changes. As a result, in multi- targets scenario, sidelobe pedestal arisen induced by inaccuracy compensation will make possible masking if one target is much stronger than the others. Based on this property of Costas-coded FH signal a high resolution rang- velocity two-dimensional imaging algorithm is studied by using sparse component analysis. Echoes can be regarded to be sparse in rang-velocity dimensions, and a sparse dictionary is constructed based on the sparsity feature, where the waveform entropy is used as the sparse measuring function. By improving the generalized regularized FOCUSS algorithm and making use of Kalman filter, the best atom can be found iteratively and high resolution in rang and velocity is realized. The algorithm is validated by simulations, and the noise tolerance as well as the time effectiveness are analyzed.
Costas-coded Frequency Hopping (FH) signal is very sensitive to velocity changes. As a result, in multi- targets scenario, sidelobe pedestal arisen induced by inaccuracy compensation will make possible masking if one target is much stronger than the others. Based on this property of Costas-coded FH signal a high resolution rang- velocity two-dimensional imaging algorithm is studied by using sparse component analysis. Echoes can be regarded to be sparse in rang-velocity dimensions, and a sparse dictionary is constructed based on the sparsity feature, where the waveform entropy is used as the sparse measuring function. By improving the generalized regularized FOCUSS algorithm and making use of Kalman filter, the best atom can be found iteratively and high resolution in rang and velocity is realized. The algorithm is validated by simulations, and the noise tolerance as well as the time effectiveness are analyzed.
2014, 36(3): 565-570.
doi: 10.3724/SP.J.1146.2013.00648
Abstract:
For the issue of the bad Direction Of Arrival (DOA) estimation accuracy entailed by not utilizing the transmitted polarization information in electromagnetic vector sensor MIMO radar, a transmitted polarization optimization algorithm is proposed based on minimizing the Cramr-Rao Bound (CRB). First, the signal model of electromagnetic vector sensor MIMO radar for DOA estimation is proposed. Second, the drawbacks of the existing fixed polarization DOA estimation algorithm are analyzed. Third, the CRB under arbitrary polarization is derived and the polarization state corresponding to the minimum CRB is computed. Finally, with the optimal polarization, the DOA can be estimated by the fixed polarization DOA estimation algorithm. The proposed algorithm can provide better estimation accuracy than the fixed polarization DOA estimation algorithm, and remain the advantages of automatic pairing between the two dimensional DOA estimation and arbitrary placement of the transmitted electromagnetic vector sensor antennas. Simulation results verify the effectiveness of the proposed algorithm.
For the issue of the bad Direction Of Arrival (DOA) estimation accuracy entailed by not utilizing the transmitted polarization information in electromagnetic vector sensor MIMO radar, a transmitted polarization optimization algorithm is proposed based on minimizing the Cramr-Rao Bound (CRB). First, the signal model of electromagnetic vector sensor MIMO radar for DOA estimation is proposed. Second, the drawbacks of the existing fixed polarization DOA estimation algorithm are analyzed. Third, the CRB under arbitrary polarization is derived and the polarization state corresponding to the minimum CRB is computed. Finally, with the optimal polarization, the DOA can be estimated by the fixed polarization DOA estimation algorithm. The proposed algorithm can provide better estimation accuracy than the fixed polarization DOA estimation algorithm, and remain the advantages of automatic pairing between the two dimensional DOA estimation and arbitrary placement of the transmitted electromagnetic vector sensor antennas. Simulation results verify the effectiveness of the proposed algorithm.
2014, 36(3): 571-576.
doi: 10.3724/SP.J.1146.2013.00604
Abstract:
Based on Digital Elevation Mode (DEM) data, satellite orbit and baseline information, a kind of fast interferometric phase simulation method is investigated and presented for spaceborne multi-baseline InSAR system. By taking advantage of forward geocoding, the match of DEM model under strict spaceborne InSAR geometry is utilized to realize multi-baseline interferometric phase generation, and the match process is further optimized by polynomial approximation and hybrid iteration. Theory analysis and simulation experiments indicate that the proposed method can improve the computation efficiency with enough phase accuracy, as well as better iteration convergence property for complicated DEM model. Consequently, the method is suitable for efficient simulation of spaceborne multi-baseline InSAR interferometric phase for large and rugged terrain.
Based on Digital Elevation Mode (DEM) data, satellite orbit and baseline information, a kind of fast interferometric phase simulation method is investigated and presented for spaceborne multi-baseline InSAR system. By taking advantage of forward geocoding, the match of DEM model under strict spaceborne InSAR geometry is utilized to realize multi-baseline interferometric phase generation, and the match process is further optimized by polynomial approximation and hybrid iteration. Theory analysis and simulation experiments indicate that the proposed method can improve the computation efficiency with enough phase accuracy, as well as better iteration convergence property for complicated DEM model. Consequently, the method is suitable for efficient simulation of spaceborne multi-baseline InSAR interferometric phase for large and rugged terrain.
2014, 36(3): 577-582.
doi: 10.3724/SP.J.1146.2013.00638
Abstract:
To reach a compromise between efficient dynamic performance and high tracking accuracy of carrier tracking loop in high-dynamic circumstance which results in large Doppler frequency and Doppler frequency rate-of-change, a fast maximum likelihood estimation method of Doppler frequency rate-of-change is proposed in this paper, and the estimation value is utilized to aid the carrier tracking loop. First, it is pointed out that the maximum likelihood estimation method of Doppler frequency and Doppler frequency rate-of-change is equivalent to the Fractional Fourier Fransform (FrFT). Second, the estimation method of Doppler frequency rate-of- change, which combines the instant self-correlation and the segmental Discrete Fourier Transform (DFT) is proposed to solve the large two-dimensional search calculation amount of the Doppler frequency and Doppler frequency rate-of-change, and the received coarse estimation value is applied to narrow down the search range. Finally, the estimation value is used in the carrier tracking loop to reduce the dynamic stress and improve the tracking accuracy. Theoretical analysis and computer simulation show that the search calculation amount falls to 5.25 percent of the original amount with Signal to Noise Ratio (SNR) -30 dB, and the Root Mean Sguare Error(RMSE) of frequency tracked is only 8.46 Hz/s, compared with the traditional carrier tracking method the tracking sensitivity can be improved more than 3 dB.
To reach a compromise between efficient dynamic performance and high tracking accuracy of carrier tracking loop in high-dynamic circumstance which results in large Doppler frequency and Doppler frequency rate-of-change, a fast maximum likelihood estimation method of Doppler frequency rate-of-change is proposed in this paper, and the estimation value is utilized to aid the carrier tracking loop. First, it is pointed out that the maximum likelihood estimation method of Doppler frequency and Doppler frequency rate-of-change is equivalent to the Fractional Fourier Fransform (FrFT). Second, the estimation method of Doppler frequency rate-of- change, which combines the instant self-correlation and the segmental Discrete Fourier Transform (DFT) is proposed to solve the large two-dimensional search calculation amount of the Doppler frequency and Doppler frequency rate-of-change, and the received coarse estimation value is applied to narrow down the search range. Finally, the estimation value is used in the carrier tracking loop to reduce the dynamic stress and improve the tracking accuracy. Theoretical analysis and computer simulation show that the search calculation amount falls to 5.25 percent of the original amount with Signal to Noise Ratio (SNR) -30 dB, and the Root Mean Sguare Error(RMSE) of frequency tracked is only 8.46 Hz/s, compared with the traditional carrier tracking method the tracking sensitivity can be improved more than 3 dB.
2014, 36(3): 583-588.
doi: 10.3724/SP.J.1146.2013.00649
Abstract:
This paper introduces the principle of?signal detection by Singular Value Decomposition (SVD), and discusses the singular values distribution characteristics of the transient signal and Gauss white noise which received from electromagnetic-pulse along the well bore. Then the definition of singular value increment is given, and the signal is distinguished easily from noise according to those singular value increments differences. On this basis, an adaptive singular value decomposition method based on selection of main singular value using singular value increment is proposed for the detection of transient signal, and the detailed flowchart of the method is illustrated. Simulation results demonstrate that, the proposed method has a good effect on distinguishing the transient faint signal from noise and the performance outperforms the typical SVD.
This paper introduces the principle of?signal detection by Singular Value Decomposition (SVD), and discusses the singular values distribution characteristics of the transient signal and Gauss white noise which received from electromagnetic-pulse along the well bore. Then the definition of singular value increment is given, and the signal is distinguished easily from noise according to those singular value increments differences. On this basis, an adaptive singular value decomposition method based on selection of main singular value using singular value increment is proposed for the detection of transient signal, and the detailed flowchart of the method is illustrated. Simulation results demonstrate that, the proposed method has a good effect on distinguishing the transient faint signal from noise and the performance outperforms the typical SVD.
2014, 36(3): 589-594.
doi: 10.3724/SP.J.1146.2013.00149
Abstract:
The method of Direction-Of-Arrival (DOA) estimation of array signals based on Compressive Sensing (CS) theory has advantages such as fewer snapshots requirement and the capacity of dealing with the coherent sources. Exploiting the CS theory on DOA estimation, one of the key issues is to construct the sparsity model of source signals. This paper proposes the systemic analysis about how the way of space-partition affects the performance of DOA estimation, and presents a new optimal sparse reconstruction model based on space-partition with equal sine interval through the analysis about coherence. The theoretical result shows that the reconstruction model based on the manifold matrix with equal sine interval is the best model in the practical application. Finally the experiments compare the reconstruction performance of the manifold matrix with equal sine interval with that of the manifold matrix with equal angle interval. This paper provides the experiment results about the performance of signal reconstruction and DOA estimation, respectively. The advantage of the presented sparsity model is verified.
The method of Direction-Of-Arrival (DOA) estimation of array signals based on Compressive Sensing (CS) theory has advantages such as fewer snapshots requirement and the capacity of dealing with the coherent sources. Exploiting the CS theory on DOA estimation, one of the key issues is to construct the sparsity model of source signals. This paper proposes the systemic analysis about how the way of space-partition affects the performance of DOA estimation, and presents a new optimal sparse reconstruction model based on space-partition with equal sine interval through the analysis about coherence. The theoretical result shows that the reconstruction model based on the manifold matrix with equal sine interval is the best model in the practical application. Finally the experiments compare the reconstruction performance of the manifold matrix with equal sine interval with that of the manifold matrix with equal angle interval. This paper provides the experiment results about the performance of signal reconstruction and DOA estimation, respectively. The advantage of the presented sparsity model is verified.
2014, 36(3): 595-600.
doi: 10.3724/SP.J.1146.2013.00434
Abstract:
In order to extract effectively the characteristics of each condition vibration signal for rolling bearing, a sensitive Intrinsic Mode Function (IMF) selection algorithm which based on Ensemble Empirical Mode Decomposition (EEMD) is proposed. First, for obtaining the initial characteristics of the vibration signal, the vibration signal is decomposed by using EEMD, and the sensitive components of obtained IMFs are extracted automatically by using kurtosis combined with correlation coefficient. Then, the feature vectors of each condition vibration signal of rolling bearing are obtained by using Singular Value Decomposition (SVD) and AutoRegressive (AR) model. The obtained feature vectors are regarded as the input of the improved hyper-sphere multi-class Support Vector Machine (SVM) for intelligent recognition. Thereby, the condition recognition of normal state, different fault types and different degrees of performance degradation of rolling bearing can be achieved. The experimental results show that, the proposed method can effectively extract fault characteristics information of rolling bearing more than EMD combined with AR model and EMD combined with SVD method, and the recognition rate is higher.
In order to extract effectively the characteristics of each condition vibration signal for rolling bearing, a sensitive Intrinsic Mode Function (IMF) selection algorithm which based on Ensemble Empirical Mode Decomposition (EEMD) is proposed. First, for obtaining the initial characteristics of the vibration signal, the vibration signal is decomposed by using EEMD, and the sensitive components of obtained IMFs are extracted automatically by using kurtosis combined with correlation coefficient. Then, the feature vectors of each condition vibration signal of rolling bearing are obtained by using Singular Value Decomposition (SVD) and AutoRegressive (AR) model. The obtained feature vectors are regarded as the input of the improved hyper-sphere multi-class Support Vector Machine (SVM) for intelligent recognition. Thereby, the condition recognition of normal state, different fault types and different degrees of performance degradation of rolling bearing can be achieved. The experimental results show that, the proposed method can effectively extract fault characteristics information of rolling bearing more than EMD combined with AR model and EMD combined with SVD method, and the recognition rate is higher.
2014, 36(3): 601-609.
doi: 10.3724/SP.J.1146.2013.00652
Abstract:
For the issue of multiple moving targets segmentation in intelligent monitoring system, an adaptive splitting and merging clustering algorithm of the moving target segmentation is proposed. First, it uses the time-domain information for foreground image segmentation through the sample variance background modeling algorithm, thus obtains the foreground image containing multiple moving targets. It defines pixel space connectivity rate and designs a perpendicular split method for the initial cluster adaptive splitting and merging. Without pre-set number of initial cluster, the self-organized iterative clustering segmentation algorithm can complete multiple moving targets segmentation. Experimental results show that the proposed algorithm is suitable for multiple moving targets segmentation, and the segmentation results are consistent with the human visual judgment. The use of space connectivity information improves the iterative algorithm convergence speed, thus it has good real-time.
For the issue of multiple moving targets segmentation in intelligent monitoring system, an adaptive splitting and merging clustering algorithm of the moving target segmentation is proposed. First, it uses the time-domain information for foreground image segmentation through the sample variance background modeling algorithm, thus obtains the foreground image containing multiple moving targets. It defines pixel space connectivity rate and designs a perpendicular split method for the initial cluster adaptive splitting and merging. Without pre-set number of initial cluster, the self-organized iterative clustering segmentation algorithm can complete multiple moving targets segmentation. Experimental results show that the proposed algorithm is suitable for multiple moving targets segmentation, and the segmentation results are consistent with the human visual judgment. The use of space connectivity information improves the iterative algorithm convergence speed, thus it has good real-time.
2014, 36(3): 610-616.
doi: 10.3724/SP.J.1146.2013.00554
Abstract:
To tackle the problem of single labeled image person face recognition, a subspace label propagation and regularized discriminant analysis based semi-supervised dimensionality reduction method is proposed in this paper. First, a label propagation method based on subspace assumption is designed to propagate the label information from labeled data to unlabeled data. Then, based on the propagated labeled dataset, regularized discriminant analysis is used to conduct dimensionality reduction. Finally, the recognition of testing face is completed in low dimensional space using nearest neighbor classifier. The extensive experiments on three publicly available face databases CMU PIE, Extended Yale B, and AR validate the feasibility and effectiveness of the proposed method.
To tackle the problem of single labeled image person face recognition, a subspace label propagation and regularized discriminant analysis based semi-supervised dimensionality reduction method is proposed in this paper. First, a label propagation method based on subspace assumption is designed to propagate the label information from labeled data to unlabeled data. Then, based on the propagated labeled dataset, regularized discriminant analysis is used to conduct dimensionality reduction. Finally, the recognition of testing face is completed in low dimensional space using nearest neighbor classifier. The extensive experiments on three publicly available face databases CMU PIE, Extended Yale B, and AR validate the feasibility and effectiveness of the proposed method.
2014, 36(3): 617-623.
doi: 10.3724/SP.J.1146.2013.00974
Abstract:
To solve the issue of background interferences on the scene text automatic localization algorithm, a scheme of background suppression for scene text is proposed, which utilizes characteristic of visual saliency to combine histogram of oriented gradient features, its statistical features, gradient magnitude features and gradient curve features with the boosting frame. The scheme aims to suppressing the complex background and highlighting the foreground text in natural scene. It can consider be as the preprocessing stage of the scene text automatic localization algorithm, and it improves the performances of the scene text automatic localization algorithm. The experimental results in both the ICDAR2011 scene text localization competition test dataset and the laboratory Chinese dataset show that the proposed scheme can suppress effectively the complex background and improve the scene text localization algorithm.
To solve the issue of background interferences on the scene text automatic localization algorithm, a scheme of background suppression for scene text is proposed, which utilizes characteristic of visual saliency to combine histogram of oriented gradient features, its statistical features, gradient magnitude features and gradient curve features with the boosting frame. The scheme aims to suppressing the complex background and highlighting the foreground text in natural scene. It can consider be as the preprocessing stage of the scene text automatic localization algorithm, and it improves the performances of the scene text automatic localization algorithm. The experimental results in both the ICDAR2011 scene text localization competition test dataset and the laboratory Chinese dataset show that the proposed scheme can suppress effectively the complex background and improve the scene text localization algorithm.
2014, 36(3): 624-630.
doi: 10.3724/SP.J.1146.2013.01155
Abstract:
A new local saliency texture descriptor named Local Ternary Number (LTN) is defined in this paper, and a new object tracking method combining LTN with hue information is proposed. Derived from Local Similarity Number (LSN), the new local saliency texture descriptor makes full use of pixel intensity relationship in a 8-connected neighbourhood. Compared with LSN, the LTN could distinguish different texture structures with the same local saliency degree. LTN mask not only extracts the key object pixels on edges, lines and corners to enhance the distinguish ability of texture feature, but also preserves the unity of the object. Then a new Mean Shift (MS) tracking method is built by utilizing the new object model, which integrating LTN with hue information from the object pixels within this mask. A large number of experiments are conducted and the experiment results demonstrate that the proposed method improve the performance of the traditional MS tracker, and the proposed method tracks object continuously and accurately even in the scene with similar color and illumination changing.
A new local saliency texture descriptor named Local Ternary Number (LTN) is defined in this paper, and a new object tracking method combining LTN with hue information is proposed. Derived from Local Similarity Number (LSN), the new local saliency texture descriptor makes full use of pixel intensity relationship in a 8-connected neighbourhood. Compared with LSN, the LTN could distinguish different texture structures with the same local saliency degree. LTN mask not only extracts the key object pixels on edges, lines and corners to enhance the distinguish ability of texture feature, but also preserves the unity of the object. Then a new Mean Shift (MS) tracking method is built by utilizing the new object model, which integrating LTN with hue information from the object pixels within this mask. A large number of experiments are conducted and the experiment results demonstrate that the proposed method improve the performance of the traditional MS tracker, and the proposed method tracks object continuously and accurately even in the scene with similar color and illumination changing.
2014, 36(3): 631-638.
doi: 10.3724/SP.J.1146.2013.00671
Abstract:
The traditional image steganalysis methods are based on the features extracted from the whole image, while ignoring the differences of the image content. A new JPEG steganalysis algorithm using quad-treebased segmentation is proposed. First, the given images are segmented to sub-images according to the texture complexity. Then, then steganalysis features of each sort of sub-images with the same or close texture complexity are extracted separately to build a classifier. Finally, the steganalysis results of the whole image are obtained by weighted fusing of all the sub-image categories. Experimental results demonstrate that the proposed algorithm exhibits excellent performance and significantly improves the detection accuracy.
The traditional image steganalysis methods are based on the features extracted from the whole image, while ignoring the differences of the image content. A new JPEG steganalysis algorithm using quad-treebased segmentation is proposed. First, the given images are segmented to sub-images according to the texture complexity. Then, then steganalysis features of each sort of sub-images with the same or close texture complexity are extracted separately to build a classifier. Finally, the steganalysis results of the whole image are obtained by weighted fusing of all the sub-image categories. Experimental results demonstrate that the proposed algorithm exhibits excellent performance and significantly improves the detection accuracy.
2014, 36(3): 639-644.
doi: 10.3724/SP.J.1146.2013.00758
Abstract:
In order to improve the passive positioning accuracy of three-element array, a modified cross- spectral algorithm is proposed for time delay difference estimation. The improved method solves phase ambiguity issue in conventional the cross-spectral method, and enhances the robustness of cross-spectral method in practical application. The time delay difference obtained with the proposed method contains cycle value and correction value. The cycle value is obtained by compensating the phase of cross-spectrum signal, and the correction value is obtained by applying least-squares to cross-spectrum signal after compensation. Theoretical analysis and experiment results show that this method can achieves the evaluation accuracy of10-6 s for sampling rate of 103 Hz, and has a strong practicability. Therefore it can effectively improve the positioning accuracy of three-element array passive positioning.
In order to improve the passive positioning accuracy of three-element array, a modified cross- spectral algorithm is proposed for time delay difference estimation. The improved method solves phase ambiguity issue in conventional the cross-spectral method, and enhances the robustness of cross-spectral method in practical application. The time delay difference obtained with the proposed method contains cycle value and correction value. The cycle value is obtained by compensating the phase of cross-spectrum signal, and the correction value is obtained by applying least-squares to cross-spectrum signal after compensation. Theoretical analysis and experiment results show that this method can achieves the evaluation accuracy of10-6 s for sampling rate of 103 Hz, and has a strong practicability. Therefore it can effectively improve the positioning accuracy of three-element array passive positioning.
2014, 36(3): 645-649.
doi: 10.3724/SP.J.1146.2013.00818
Abstract:
Proxy re-signature is an important tool for simplifying key management, and can be used to prove a proof for a path, manage group signatures, simplify certificate management and so on. Currently, proxy re- signature schemes are based on large integer factorization and discrete logarithm which are not security in quantum setting. For this problem, the first identity-based proxy re-signature scheme over lattices is constructed in this paper, which uses preimage sampleable technology and lattice basis delegation in fixed dimension technology. Its security is based on the hardness of Small Integer Solution (SIS) problem. This scheme possesses the properties of unidirectional, multi-use and so on. Compared with the previous schemes which have the same properties, the proposed scheme has the advantage of low verification cost and low asymptotic computational complexity.
Proxy re-signature is an important tool for simplifying key management, and can be used to prove a proof for a path, manage group signatures, simplify certificate management and so on. Currently, proxy re- signature schemes are based on large integer factorization and discrete logarithm which are not security in quantum setting. For this problem, the first identity-based proxy re-signature scheme over lattices is constructed in this paper, which uses preimage sampleable technology and lattice basis delegation in fixed dimension technology. Its security is based on the hardness of Small Integer Solution (SIS) problem. This scheme possesses the properties of unidirectional, multi-use and so on. Compared with the previous schemes which have the same properties, the proposed scheme has the advantage of low verification cost and low asymptotic computational complexity.
2014, 36(3): 650-654.
doi: 10.3724/SP.J.1146.2013.00751
Abstract:
A new class of generalized cyclotomic sequence with period2pq is proposed in this paper, wherep andq are distinct primes. A formula for computing the linear complexity of the proposed sequence is also given. With the knowledge of the support set of the generalized cyclotomic sequence, its linear complexity can be easily determined using the formula.
A new class of generalized cyclotomic sequence with period2pq is proposed in this paper, wherep andq are distinct primes. A formula for computing the linear complexity of the proposed sequence is also given. With the knowledge of the support set of the generalized cyclotomic sequence, its linear complexity can be easily determined using the formula.
2014, 36(3): 655-661.
doi: 10.3724/SP.J.1146.2013.00659
Abstract:
Without the priori information of interference system, iterative detection algorithm based on minimum- error-rate threshold can make a good performance. In practice, however, accurate noise estimation is difficult to achieve because of low SNR, which results in a large deviation between the iterative convergence threshold and the minimum-error-rate threshold, and then causes a deterioration in detection performance. To address these issues, an improved iterative detection algorithm is proposed in this paper. Meanwhile, the iterative estimation expression of noise power, signal power and signal occupancy rate are given by detailed derivation. In addition, the constrained relationship between detection performance and SNR is discussed, and the closed-form expression of the minimum SNR is proposed to meet certain performance indicators. The simulation results show the effectiveness of the proposed algorithm.
Without the priori information of interference system, iterative detection algorithm based on minimum- error-rate threshold can make a good performance. In practice, however, accurate noise estimation is difficult to achieve because of low SNR, which results in a large deviation between the iterative convergence threshold and the minimum-error-rate threshold, and then causes a deterioration in detection performance. To address these issues, an improved iterative detection algorithm is proposed in this paper. Meanwhile, the iterative estimation expression of noise power, signal power and signal occupancy rate are given by detailed derivation. In addition, the constrained relationship between detection performance and SNR is discussed, and the closed-form expression of the minimum SNR is proposed to meet certain performance indicators. The simulation results show the effectiveness of the proposed algorithm.
2014, 36(3): 662-668.
doi: 10.3724/SP.J.1146.2013.00717
Abstract:
Co-time Co-frequency Full-Duplex (CCFD) radio transmission will cause a strong self-interference in its receiver. To ensure the undistorted transmission in the Radio Frequency (RF) channel and effective sampling of the desired signal, the Self-Interference Cancellation (SIC) need to be applied to RF frontend. In this paper, the CCFD verification experiment is presented based on the Long Term Evolution (LTE) that adopts RF SIC with the coupled RF transmitted signal. Considering the direct path self-interference between transmit and receive antennas, the relationship among interference power, interference bandwidth, RF adjustment errors and SIC ability is analyzed. Consequently, the expression of SIC ability is derived. Analysis and experimental results show that the SIC abilities are 54 dB in theory and 51.2 dB in practice for a 20 MHz LTE signal with received power of -10 dBm.
Co-time Co-frequency Full-Duplex (CCFD) radio transmission will cause a strong self-interference in its receiver. To ensure the undistorted transmission in the Radio Frequency (RF) channel and effective sampling of the desired signal, the Self-Interference Cancellation (SIC) need to be applied to RF frontend. In this paper, the CCFD verification experiment is presented based on the Long Term Evolution (LTE) that adopts RF SIC with the coupled RF transmitted signal. Considering the direct path self-interference between transmit and receive antennas, the relationship among interference power, interference bandwidth, RF adjustment errors and SIC ability is analyzed. Consequently, the expression of SIC ability is derived. Analysis and experimental results show that the SIC abilities are 54 dB in theory and 51.2 dB in practice for a 20 MHz LTE signal with received power of -10 dBm.
2014, 36(3): 669-675.
doi: 10.3724/SP.J.1146.2013.00509
Abstract:
For short burst communication systems, the position and the number of pilot symbols have a great impact on frequency estimation accuracy and estimation range in time-domain correlation frequency estimation algorithm. So a frequency estimation algorithm with a high frequency estimation accuracy based on the summation of the entire cross correlation is proposed, and its theoretical estimation variance is derived. By analyzing the impact of the pilot position on estimation accuracy and estimation range, a scheme of Variable D-spaced Preamble Middle (VDPM) frame structure is proposed which can choose the distance of pilot blocks according to estimation accuracy and estimation range. Theoretical analysis and simulation results show that the frame structure can satisfy the requirements of frequency estimation range and estimation accuracy, and the estimation algorithm can achieve high estimation accuracy with a few pilot symbols, hence it is suit for short burst communication system.
For short burst communication systems, the position and the number of pilot symbols have a great impact on frequency estimation accuracy and estimation range in time-domain correlation frequency estimation algorithm. So a frequency estimation algorithm with a high frequency estimation accuracy based on the summation of the entire cross correlation is proposed, and its theoretical estimation variance is derived. By analyzing the impact of the pilot position on estimation accuracy and estimation range, a scheme of Variable D-spaced Preamble Middle (VDPM) frame structure is proposed which can choose the distance of pilot blocks according to estimation accuracy and estimation range. Theoretical analysis and simulation results show that the frame structure can satisfy the requirements of frequency estimation range and estimation accuracy, and the estimation algorithm can achieve high estimation accuracy with a few pilot symbols, hence it is suit for short burst communication system.
2014, 36(3): 676-682.
doi: 10.3724/SP.J.1146.2013.00551
Abstract:
According to the characteristics of the store and forward LEO communication satellite constellation and the issue that the traditional constellation design methods can not optimizes simultaneously the coverage performance and network performance, a new store and forward communication satellite constellation design method which balances the coverage and network performance, is proposed, and the Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize this multi-objective and multi-constrained constellation design. A collaborative optimization simulation platform based on STK and OPNET is built，and the simulation result shows the effectiveness of the proposed constellation design methods.
According to the characteristics of the store and forward LEO communication satellite constellation and the issue that the traditional constellation design methods can not optimizes simultaneously the coverage performance and network performance, a new store and forward communication satellite constellation design method which balances the coverage and network performance, is proposed, and the Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize this multi-objective and multi-constrained constellation design. A collaborative optimization simulation platform based on STK and OPNET is built，and the simulation result shows the effectiveness of the proposed constellation design methods.
2014, 36(3): 683-689.
doi: 10.3724/SP.J.1146.2013.00722
Abstract:
A SNR estimator based on packet error ratio is proposed，and its statistical property is analyzed for the interference problem in multiple readers environment. An adaptive weighted proportion fairness power allocation algorithm is proposed which can increase the weight of readers in high density area automatically to ensure the read performance for readers in different position. A distributed algorithm is applied to power allocation and its convergence to a local solution is proved. The simulation results show that，the fairness and convergence of the proposed algorithm are superior to the existed allocation scheme.
A SNR estimator based on packet error ratio is proposed，and its statistical property is analyzed for the interference problem in multiple readers environment. An adaptive weighted proportion fairness power allocation algorithm is proposed which can increase the weight of readers in high density area automatically to ensure the read performance for readers in different position. A distributed algorithm is applied to power allocation and its convergence to a local solution is proved. The simulation results show that，the fairness and convergence of the proposed algorithm are superior to the existed allocation scheme.
2014, 36(3): 690-695.
doi: 10.3724/SP.J.1146.2013.00667
Abstract:
In environmental monitoring applications, there are often various objects to be monitored by sensor networks. In this scenario, each heterogeneous node carries some different sensors, and the coverage of multiple areas is required in order to monitor every different subobject. In sensor networks with random distributed nodes, an average subnet lifetime model is proposed to evaluate the average lifetime of nodes sensing one subobject. Given the constraints of cost budget and area coverage of different objects, a multi-objective multi-coverage algorithm based on integer vector programming is proposed to balance the cost and coverage performance, as well as the monitoring life of different subobjects. The algorithm is divided into two steps. The first step is to compute the number of each type of sensors used to monitor one subobject, and the second step is to determine the number of different kinds of heterogeneous nodes based on the average subnet life model. To solve the proposed vector programming issues, two suboptimal methods are given. In the simulation experiments, different suboptimal methods are compared, and the computational complexity of the proposed algorithm is analysed. Simulation examples verify the effectiveness of the proposed algorithm in the multi-objects monitoring applications.
In environmental monitoring applications, there are often various objects to be monitored by sensor networks. In this scenario, each heterogeneous node carries some different sensors, and the coverage of multiple areas is required in order to monitor every different subobject. In sensor networks with random distributed nodes, an average subnet lifetime model is proposed to evaluate the average lifetime of nodes sensing one subobject. Given the constraints of cost budget and area coverage of different objects, a multi-objective multi-coverage algorithm based on integer vector programming is proposed to balance the cost and coverage performance, as well as the monitoring life of different subobjects. The algorithm is divided into two steps. The first step is to compute the number of each type of sensors used to monitor one subobject, and the second step is to determine the number of different kinds of heterogeneous nodes based on the average subnet life model. To solve the proposed vector programming issues, two suboptimal methods are given. In the simulation experiments, different suboptimal methods are compared, and the computational complexity of the proposed algorithm is analysed. Simulation examples verify the effectiveness of the proposed algorithm in the multi-objects monitoring applications.
2014, 36(3): 696-702.
doi: 10.3724/SP.J.1146.2013.00730
Abstract:
For the problem of coverage blind area generated by randomly deploying the heterogeneous nodes in the initial stage, and inspired by simple random sampling in probability theory and optimization algorithm, a coverage optimization algorithm for heterogeneous sensing radius in Wireless Sensor Networks (WSNs) is proposed. To minimize the sensor nodes moving distance and improve the coverage rate, a quadratic programming mathematic model is established according to the relationship between coordinates of the intersections that between the sensing circles and the sampling line segments. Meanwhile, the coverage of plane will be optimized when more line segments get optimizing coverage. Simulation results show that the algorithm improves the coverage rate of homogeneous networks effectively.
For the problem of coverage blind area generated by randomly deploying the heterogeneous nodes in the initial stage, and inspired by simple random sampling in probability theory and optimization algorithm, a coverage optimization algorithm for heterogeneous sensing radius in Wireless Sensor Networks (WSNs) is proposed. To minimize the sensor nodes moving distance and improve the coverage rate, a quadratic programming mathematic model is established according to the relationship between coordinates of the intersections that between the sensing circles and the sampling line segments. Meanwhile, the coverage of plane will be optimized when more line segments get optimizing coverage. Simulation results show that the algorithm improves the coverage rate of homogeneous networks effectively.
2014, 36(3): 703-707.
doi: 10.3724/SP.J.1146.2013.00559
Abstract:
To motivate nodes to forward packets in Ad hoc networks under the condition of imperfect information, repeated game is often used to model the process of sequential interactions between nodes and the Bellman equations is applied to design strategy based on sequential equilibrium. The nodes need not to exchange their monitor information, so it saves nodes energy and reduces the network burden. Compared with existing sequential equilibrium strategy, since the proposed strategy does not use trigger mechanism, which is sensible to observation error, it improves the cooperation rate and the average benefits of networks with imperfect information. Simulation compares the performance of two sequential equilibrium strategies. The results indicate that the proposed strategy not only improves the cooperation rate, but also has a good adaptability.
To motivate nodes to forward packets in Ad hoc networks under the condition of imperfect information, repeated game is often used to model the process of sequential interactions between nodes and the Bellman equations is applied to design strategy based on sequential equilibrium. The nodes need not to exchange their monitor information, so it saves nodes energy and reduces the network burden. Compared with existing sequential equilibrium strategy, since the proposed strategy does not use trigger mechanism, which is sensible to observation error, it improves the cooperation rate and the average benefits of networks with imperfect information. Simulation compares the performance of two sequential equilibrium strategies. The results indicate that the proposed strategy not only improves the cooperation rate, but also has a good adaptability.
2014, 36(3): 708-714.
doi: 10.3724/SP.J.1146.2013.00755
Abstract:
The network virtualization requires real-time monitoring of the substrate network resources state. An efficient monitoring policy should reduce the transmission delay and bandwidth of state information collection. For this objective, a resource monitoring policy based on monitoring agents is designed. This policy formulates the issue of monitoring agents deployment as a 0-1 programming problem, which is solved by the advanced quantum genetic algorithm. Evaluations show that the scheme of monitoring agents deployment framed by the proposed policy has outstanding performance in reducing communication cost.
The network virtualization requires real-time monitoring of the substrate network resources state. An efficient monitoring policy should reduce the transmission delay and bandwidth of state information collection. For this objective, a resource monitoring policy based on monitoring agents is designed. This policy formulates the issue of monitoring agents deployment as a 0-1 programming problem, which is solved by the advanced quantum genetic algorithm. Evaluations show that the scheme of monitoring agents deployment framed by the proposed policy has outstanding performance in reducing communication cost.
2014, 36(3): 715-720.
doi: 10.3724/SP.J.1146.2013.00534
Abstract:
The matrix factorization is one of the most powerful tools in collaborative filtering recommender systems. The Bayesian Probabilistic Matrix Factorization (BPMF) model has advantages of high prediction accuracy, but can not capture non-linear relationships between latent factors. To address this problem, an improved model is proposed based on the Logistic function and Markov Chain Monte Carlo is used to train the proposed model. Experiments on two real-world benchmark datasets show significant improvements in prediction accuracy compared with several state-of-the-art methods for recommendation tasks.
The matrix factorization is one of the most powerful tools in collaborative filtering recommender systems. The Bayesian Probabilistic Matrix Factorization (BPMF) model has advantages of high prediction accuracy, but can not capture non-linear relationships between latent factors. To address this problem, an improved model is proposed based on the Logistic function and Markov Chain Monte Carlo is used to train the proposed model. Experiments on two real-world benchmark datasets show significant improvements in prediction accuracy compared with several state-of-the-art methods for recommendation tasks.
2014, 36(3): 721-727.
doi: 10.3724/SP.J.1146.2013.00636
Abstract:
Considering the color aliasing caused by down-sampling in display systems, a novel color anti-aliasing filtering method based on the subpixel arrangements of displays is proposed. Due to the shape and the area of color aliasing are closely related with the diversity of arrangements, the Nyquist limits of different primary colors within various arrangements are obtained in frequency domain by reciprocal lattice theory, and the anti-aliasing filters applied to different primary colors are designed. To suppress color aliasing efficiently while keeping more original image details, the images are reconstructed and displayed through subpixel sampling after preprocessed by them. Analysis and experiments show that when the clarity of display images is measured by the PSNR at the luminance component, the method proposed in this paper can increase the PSNR nearly 30% than 5-tap filtering. At the same time, the method is simple and easy to implement.
Considering the color aliasing caused by down-sampling in display systems, a novel color anti-aliasing filtering method based on the subpixel arrangements of displays is proposed. Due to the shape and the area of color aliasing are closely related with the diversity of arrangements, the Nyquist limits of different primary colors within various arrangements are obtained in frequency domain by reciprocal lattice theory, and the anti-aliasing filters applied to different primary colors are designed. To suppress color aliasing efficiently while keeping more original image details, the images are reconstructed and displayed through subpixel sampling after preprocessed by them. Analysis and experiments show that when the clarity of display images is measured by the PSNR at the luminance component, the method proposed in this paper can increase the PSNR nearly 30% than 5-tap filtering. At the same time, the method is simple and easy to implement.
2014, 36(3): 728-733.
doi: 10.3724/SP.J.1146.2013.00587
Abstract:
For the complex structures, the narrow space and the large quantity of equipments in the helicopter, a complicated electromagnetic environment makes effects in the avionics platform. For the purpose of finding the ElectroMagnetic Interference (EMI) coupling path rapidly, a method for determining EMI coupling path is presented. Based on the minimum electromagnetic attenuation, the EMI coupling network is converted into EMI coupling diagraph. In a specified frequency, Dijkstra algorithm is applied to seek the shortest path between interfering source and victim. Then a weak link of the electronic system will be determined. Based on this method, a simulation of processors and radio system in helicopter is carried out, and the main coupling path is successfully established. Simulation and analysis indicate that the proposed method is able to find out the weak links of electronic system in an effective way and support for the solution of electromagnetic compatibility issues.
For the complex structures, the narrow space and the large quantity of equipments in the helicopter, a complicated electromagnetic environment makes effects in the avionics platform. For the purpose of finding the ElectroMagnetic Interference (EMI) coupling path rapidly, a method for determining EMI coupling path is presented. Based on the minimum electromagnetic attenuation, the EMI coupling network is converted into EMI coupling diagraph. In a specified frequency, Dijkstra algorithm is applied to seek the shortest path between interfering source and victim. Then a weak link of the electronic system will be determined. Based on this method, a simulation of processors and radio system in helicopter is carried out, and the main coupling path is successfully established. Simulation and analysis indicate that the proposed method is able to find out the weak links of electronic system in an effective way and support for the solution of electromagnetic compatibility issues.
2014, 36(3): 734-738.
doi: 10.3724/SP.J.1146.2013.00707
Abstract:
For the issue that escort jamming in main-lobe can not be countered by radar, a main-lobe jamming suppression technique about multistatic radar is studied, and the Adaptive Main-lobe Jamming Cancellation Algorithm based on Block Preconditioning (BP-AMJCA) is proposed in this paper. Firstly, block preconditioning is combined with direct matrix inversion to get the initial weight vector, then High Order Cumulants is introduced to Variable Forgetting Factor Recursive Least Square (HOC-VFF-RLS) Algorithm to realize the update of weights. Compared with traditional Adaptive Main-lobe Jamming Cancellation Algorithm based on Least Mean Square (LMS-AMJCA), the proposed algorithm has little complexity increase, fast convergent rate and good robustness. The simulation experiment result of main-lobe jamming suppression shows that the issue of target echo signal cancellation in main-lobe is solved, and the output SINR of two receivers is improved to 35-40 dB by BP-AMJCA algorithm, which has important application value.
For the issue that escort jamming in main-lobe can not be countered by radar, a main-lobe jamming suppression technique about multistatic radar is studied, and the Adaptive Main-lobe Jamming Cancellation Algorithm based on Block Preconditioning (BP-AMJCA) is proposed in this paper. Firstly, block preconditioning is combined with direct matrix inversion to get the initial weight vector, then High Order Cumulants is introduced to Variable Forgetting Factor Recursive Least Square (HOC-VFF-RLS) Algorithm to realize the update of weights. Compared with traditional Adaptive Main-lobe Jamming Cancellation Algorithm based on Least Mean Square (LMS-AMJCA), the proposed algorithm has little complexity increase, fast convergent rate and good robustness. The simulation experiment result of main-lobe jamming suppression shows that the issue of target echo signal cancellation in main-lobe is solved, and the output SINR of two receivers is improved to 35-40 dB by BP-AMJCA algorithm, which has important application value.
2014, 36(3): 739-743.
doi: 10.3724/SP.J.1146.2013.01178
Abstract:
This paper proposes a novel and low-complexity adaptive Chase iterative decoding algorithm for Turbo Product Codes (TPCs). Different from the previous reported results, during decoding, the new adaptive algorithm is based on the statistics of the number of the candidate sequences with the same minimum squared Euclidean distance in each row or column of TPC block firstly, and then the Least Reliable Bits (LRBs) can change according to the statistical results via the proposed steps. It can be verified by Monte Carlo simulations, when using the same extended Hamming code as TPC subcodes with coding efficiency of 0.879 and the Bit Error Rate (BER) is 10-4, the coding loss of the proposed adaptive algorithm is just about 0.08 dB compared with Pyndiahs iterative decoding algorithm using the fixed LRBs parameter in Chase decoder, but the average complexity of the proposed algorithm could be reduced about 40.4%.
This paper proposes a novel and low-complexity adaptive Chase iterative decoding algorithm for Turbo Product Codes (TPCs). Different from the previous reported results, during decoding, the new adaptive algorithm is based on the statistics of the number of the candidate sequences with the same minimum squared Euclidean distance in each row or column of TPC block firstly, and then the Least Reliable Bits (LRBs) can change according to the statistical results via the proposed steps. It can be verified by Monte Carlo simulations, when using the same extended Hamming code as TPC subcodes with coding efficiency of 0.879 and the Bit Error Rate (BER) is 10-4, the coding loss of the proposed adaptive algorithm is just about 0.08 dB compared with Pyndiahs iterative decoding algorithm using the fixed LRBs parameter in Chase decoder, but the average complexity of the proposed algorithm could be reduced about 40.4%.
2014, 36(3): 744-748.
doi: 10.3724/SP.J.1146.2013.00777
Abstract:
To deal with the degradation of wireless sensor network routing efficiency caused by voids, Energy Efficiency Multi-channel Coordination Routing algorithm based on 3D cell space (3D-EEMCR) is presented in this paper. According to the energy consumption model, the algorithm balances residual energy and location information of the nodes to select the cell leader node, so as to balance the energy consumption of network. In addition, the algorithm adopts perimeter routing mode which uses the mutual assistance of the main channel and the assistant channels to route around void areas. The simulation results show that 3D-EEMCR effectively improves the message packet delivery rate, reduces the average energy consumption of the network, and extends the network lifetime in comparison with 3D-GPR (Grid Position-based Routing) and 3D-CSR (Cell Space Routing).
To deal with the degradation of wireless sensor network routing efficiency caused by voids, Energy Efficiency Multi-channel Coordination Routing algorithm based on 3D cell space (3D-EEMCR) is presented in this paper. According to the energy consumption model, the algorithm balances residual energy and location information of the nodes to select the cell leader node, so as to balance the energy consumption of network. In addition, the algorithm adopts perimeter routing mode which uses the mutual assistance of the main channel and the assistant channels to route around void areas. The simulation results show that 3D-EEMCR effectively improves the message packet delivery rate, reduces the average energy consumption of the network, and extends the network lifetime in comparison with 3D-GPR (Grid Position-based Routing) and 3D-CSR (Cell Space Routing).
2014, 36(3): 749-753.
doi: 10.3724/SP.J.1146.2013.00598
Abstract:
A novel Opportunistic-Network-Coding based Weighted broadcasting Retransmission (WONCR) approach is proposed to deal with the problem of data dissemination scheme based on opportunistic network coding in wireless broadcasting networks, which are under the conditions of high packet loss probability and different state of links. This approach implements a new scheduling algorithm based on the Weighted Packet Distribution Matrix (WPDM) to realize the selection of coded packets before XOR coding and retransmitting. The analysis and simulations show that the transmission efficiency is improved significantly and the computational complexity is low. Hence, the high-efficiency and reliable data dissemination are achieved in wireless broadcasting networks.
A novel Opportunistic-Network-Coding based Weighted broadcasting Retransmission (WONCR) approach is proposed to deal with the problem of data dissemination scheme based on opportunistic network coding in wireless broadcasting networks, which are under the conditions of high packet loss probability and different state of links. This approach implements a new scheduling algorithm based on the Weighted Packet Distribution Matrix (WPDM) to realize the selection of coded packets before XOR coding and retransmitting. The analysis and simulations show that the transmission efficiency is improved significantly and the computational complexity is low. Hence, the high-efficiency and reliable data dissemination are achieved in wireless broadcasting networks.
2014, 36(3): 754-757.
doi: 10.3724/SP.J.1146.2013.00566
Abstract:
In order to improve the emission performance of cathodes to meet the demands of new type devices, this paper develops a new-type scandate cathode coated with W+BaO-Sc2O3-SrO film prepared by Pulse Laser Deposition (PLD) technology. The experiment obtains emission current characteristics measured as a function of voltage and temperature and analyzes the emission mechanism. The test results indicate that at 1100C the current density of the new cathode reaches 305.5 A/cm2; and the layer of Ba-Sc-Sr-O is the key to this excellent performance. The abnormal Schottky effect that the cathode appears is also investigated by using semiconductor model.
In order to improve the emission performance of cathodes to meet the demands of new type devices, this paper develops a new-type scandate cathode coated with W+BaO-Sc2O3-SrO film prepared by Pulse Laser Deposition (PLD) technology. The experiment obtains emission current characteristics measured as a function of voltage and temperature and analyzes the emission mechanism. The test results indicate that at 1100C the current density of the new cathode reaches 305.5 A/cm2; and the layer of Ba-Sc-Sr-O is the key to this excellent performance. The abnormal Schottky effect that the cathode appears is also investigated by using semiconductor model.
2014, 36(3): 758-762.
doi: 10.3724/SP.J.1146.2013.00704
Abstract:
A new pseudo natural sampling algorithm is proposed in this paper for correcting the harmonic distortion produced by switching signal modulation in Uniform sampled Pulse Width Modulation (UPWM) digital class D power amplifiers. This algorithm combines the 3th-order and 1st-order Lagrange interpolation methods and adopts a position judging method for pseudo natural sampling point to obtain an expected harmonic distortion correction effect and computation complexity. A switching signal modulator test system based on FPGA is built to test the proposed algorithm and other kindred algorithms. The test results show that the proposed algorithm basically eliminates the harmonic distortion with modest hardware consumption and is better than other kindred algorithms.
A new pseudo natural sampling algorithm is proposed in this paper for correcting the harmonic distortion produced by switching signal modulation in Uniform sampled Pulse Width Modulation (UPWM) digital class D power amplifiers. This algorithm combines the 3th-order and 1st-order Lagrange interpolation methods and adopts a position judging method for pseudo natural sampling point to obtain an expected harmonic distortion correction effect and computation complexity. A switching signal modulator test system based on FPGA is built to test the proposed algorithm and other kindred algorithms. The test results show that the proposed algorithm basically eliminates the harmonic distortion with modest hardware consumption and is better than other kindred algorithms.
