A new iterative greedy algorithm based on the backtracking technique was proposed for distributed compressed sensing(DCS) problem. The algorithm applies two mechanisms for precise recovery soft thresholding and cuttin...A new iterative greedy algorithm based on the backtracking technique was proposed for distributed compressed sensing(DCS) problem. The algorithm applies two mechanisms for precise recovery soft thresholding and cutting. It can reconstruct several compressed signals simultaneously even without any prior information of the sparsity, which makes it a potential candidate for many practical applications, but the numbers of non-zero(significant) coefficients of signals are not available. Numerical experiments are conducted to demonstrate the validity and high performance of the proposed algorithm, as compared to other existing strong DCS algorithms.展开更多
For ship targets with complex motion,it is difficult for the traditional monostatic inverse synthetic aperture radar(ISAR)imaging to improve the cross-range resolution by increasing of accumulation time.In this paper,...For ship targets with complex motion,it is difficult for the traditional monostatic inverse synthetic aperture radar(ISAR)imaging to improve the cross-range resolution by increasing of accumulation time.In this paper,a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target.Multiple stations are used to observe the target in a short time,thereby the effect of incoherence caused by the complex motion of the ship can be reduced.The signal model of ship target with three-dimensional(3-D)rotation is constructed firstly.Then detailed analysis about the improvement of crossrange resolution is presented.Afterward,we propose the methods of parameters estimation to solve the problem of the overlap or gap,which will cause a loss of resolution and is necessary for subsequent processing.Besides,the compressed sensing(CS)method is applied to reconstruct the echoes with gaps.Finally,numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.展开更多
为改善分布式压缩视频感知（distributed compressive video sensing，DCVS）系统的视频帧图像重构质量，以实时视频传输为应用场景，提出了一种基于双重稀疏模型的图像解码算法。解码端由相邻的已重构关键帧产生边信息（sideinformatio...为改善分布式压缩视频感知（distributed compressive video sensing，DCVS）系统的视频帧图像重构质量，以实时视频传输为应用场景，提出了一种基于双重稀疏模型的图像解码算法。解码端由相邻的已重构关键帧产生边信息（sideinformation，SI）；根据双重稀疏模型思想，分离样本图像小波域下不同尺度的子带，分别使用K均值奇异值分解（K-means singular value decomposition，K—SVD）算法得到具有多尺度特性的冗余字典，结合梯度投影稀疏重建（gradient pursuit for sparsereconstruction，GPSR）算法，完成对非关键帧的重构。仿真结果表明，在相同压缩率下，相比传统K—SVD字典训练方法，本文所提出的方法对应的视频帧图像重构峰值信噪比（peak signal to noise ratio，PSNR）可获得0．5～1．5dB以上的增益。展开更多
How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to t...How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to the large number of antennas. To reduce the overwhelming pilot overhead, a hybrid orthogonal and non-orthogonal pilot distribution at the base station(BS),which is a generalization of the existing pilot distribution scheme,is proposed by exploiting the common sparsity of channel due to the compact antenna arrangement. Then the block sparsity for antennas with hybrid pilot distribution is derived respectively and can be used to obtain channel impulse response. By employing the theoretical analysis of block sparse recovery, the total coherence criterion is proposed to optimize the sensing matrix composed by orthogonal pilots. Due to the huge complexity of optimal pilot acquisition, a genetic algorithm based pilot allocation(GAPA) algorithm is proposed to acquire optimal pilot distribution locations with fast convergence. Furthermore, the Cramer Rao lower bound is derived for non-orthogonal pilot-based channel estimation and can be asymptotically approached by the prior support set, especially when the optimized pilot is employed.展开更多
针对声压传感器条件下,声呐成像的左右模糊问题;针对常规MIMO声呐成像算法分辨力受瑞利限的限制问题;针对压缩感知算法重构信号中的数值不稳定问题,本文利用声矢量传感器接收到的信号振速信息和声压信息,利用目标在空间域分布的稀疏性,...针对声压传感器条件下,声呐成像的左右模糊问题;针对常规MIMO声呐成像算法分辨力受瑞利限的限制问题;针对压缩感知算法重构信号中的数值不稳定问题,本文利用声矢量传感器接收到的信号振速信息和声压信息,利用目标在空间域分布的稀疏性,在压缩感知理论下,提出了基于声矢量传感器的二维坐标下降法(DCD)算法改进的正交匹配追踪(OMP)算法。仿真结果表明,提出的算法可以精准地估计出空间目标的方位;与传统的分布式MIMO成像算法反向投影(Back Projection,BP)相比,使用更少的实验数据,降低了运算的复杂度;当信噪比为10 d B的条件下,BP算法当主瓣级为0 d B时,在x,y,z轴最大的旁瓣级分别为–24.5 d B,–24.3 d B,–5.5 d B,而提出的算法可以获得一个稀疏解,且有效的避免左右模糊问题;避免重构信号中的矩阵求逆运算,数值不稳定得到了解决;并在信噪比为–5 d B以下时,定位精度高于声压OMP-DCD算法,具有更高的抗噪声能力和系统辨识能力。展开更多
基金Projects(61203287,61302138,11126274)supported by the National Natural Science Foundation of ChinaProject(2013CFB414)supported by Natural Science Foundation of Hubei Province,ChinaProject(CUGL130247)supported by the Special Fund for Basic Scientific Research of Central Colleges of China University of Geosciences
文摘A new iterative greedy algorithm based on the backtracking technique was proposed for distributed compressed sensing(DCS) problem. The algorithm applies two mechanisms for precise recovery soft thresholding and cutting. It can reconstruct several compressed signals simultaneously even without any prior information of the sparsity, which makes it a potential candidate for many practical applications, but the numbers of non-zero(significant) coefficients of signals are not available. Numerical experiments are conducted to demonstrate the validity and high performance of the proposed algorithm, as compared to other existing strong DCS algorithms.
基金Supported by National Natural Science Foundation of China（61170147） Major Cooperation Project of Production and College in Fujian Province（2012H61010016） Natural Science Foundation of Fujian Province（2013J01234）
基金supported by the National Natural Science Foundation of China(61871146)the Fundamental Research Funds for the Central Universities(FRFCU5710093720)。
文摘For ship targets with complex motion,it is difficult for the traditional monostatic inverse synthetic aperture radar(ISAR)imaging to improve the cross-range resolution by increasing of accumulation time.In this paper,a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target.Multiple stations are used to observe the target in a short time,thereby the effect of incoherence caused by the complex motion of the ship can be reduced.The signal model of ship target with three-dimensional(3-D)rotation is constructed firstly.Then detailed analysis about the improvement of crossrange resolution is presented.Afterward,we propose the methods of parameters estimation to solve the problem of the overlap or gap,which will cause a loss of resolution and is necessary for subsequent processing.Besides,the compressed sensing(CS)method is applied to reconstruct the echoes with gaps.Finally,numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.
文摘为改善分布式压缩视频感知（distributed compressive video sensing，DCVS）系统的视频帧图像重构质量，以实时视频传输为应用场景，提出了一种基于双重稀疏模型的图像解码算法。解码端由相邻的已重构关键帧产生边信息（sideinformation，SI）；根据双重稀疏模型思想，分离样本图像小波域下不同尺度的子带，分别使用K均值奇异值分解（K-means singular value decomposition，K—SVD）算法得到具有多尺度特性的冗余字典，结合梯度投影稀疏重建（gradient pursuit for sparsereconstruction，GPSR）算法，完成对非关键帧的重构。仿真结果表明，在相同压缩率下，相比传统K—SVD字典训练方法，本文所提出的方法对应的视频帧图像重构峰值信噪比（peak signal to noise ratio，PSNR）可获得0．5～1．5dB以上的增益。
基金supported by the National Natural Science Foundation of China(61671176 61671173)the Fundamental Research Funds for the Center Universities(HIT.MKSTISP.2016 13)
文摘How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to the large number of antennas. To reduce the overwhelming pilot overhead, a hybrid orthogonal and non-orthogonal pilot distribution at the base station(BS),which is a generalization of the existing pilot distribution scheme,is proposed by exploiting the common sparsity of channel due to the compact antenna arrangement. Then the block sparsity for antennas with hybrid pilot distribution is derived respectively and can be used to obtain channel impulse response. By employing the theoretical analysis of block sparse recovery, the total coherence criterion is proposed to optimize the sensing matrix composed by orthogonal pilots. Due to the huge complexity of optimal pilot acquisition, a genetic algorithm based pilot allocation(GAPA) algorithm is proposed to acquire optimal pilot distribution locations with fast convergence. Furthermore, the Cramer Rao lower bound is derived for non-orthogonal pilot-based channel estimation and can be asymptotically approached by the prior support set, especially when the optimized pilot is employed.
文摘针对声压传感器条件下,声呐成像的左右模糊问题;针对常规MIMO声呐成像算法分辨力受瑞利限的限制问题;针对压缩感知算法重构信号中的数值不稳定问题,本文利用声矢量传感器接收到的信号振速信息和声压信息,利用目标在空间域分布的稀疏性,在压缩感知理论下,提出了基于声矢量传感器的二维坐标下降法(DCD)算法改进的正交匹配追踪(OMP)算法。仿真结果表明,提出的算法可以精准地估计出空间目标的方位;与传统的分布式MIMO成像算法反向投影(Back Projection,BP)相比,使用更少的实验数据,降低了运算的复杂度;当信噪比为10 d B的条件下,BP算法当主瓣级为0 d B时,在x,y,z轴最大的旁瓣级分别为–24.5 d B,–24.3 d B,–5.5 d B,而提出的算法可以获得一个稀疏解,且有效的避免左右模糊问题;避免重构信号中的矩阵求逆运算,数值不稳定得到了解决;并在信噪比为–5 d B以下时,定位精度高于声压OMP-DCD算法,具有更高的抗噪声能力和系统辨识能力。
