基于压缩感知的MIMO雷达空时回波信号联合稀疏表示
发布时间：2018-08-26 12:44
【摘要】：多输入多输出(MIMO)雷达作为一种新体制雷达,与传统雷达相比,由于维数的增加面临着海量数据处理等问题。而雷达探测目标相对于背景的高度稀疏为压缩感知技术的应用提供了可能,基于压缩感知技术的雷达信号处理已成为雷达领域研究热点。在低信噪比探测条件下,压缩感知的重构性能将大幅度降低甚至失效,并且感知矩阵的等距同构条件使得脉冲积累技术难以实现。本文针对如何在压缩感知MIMO雷达中实现多脉冲信息的利用来提高信噪比,研究了基于压缩感知的MIMO雷达空时回波信号联合稀疏表示方式,以及一种针对压缩感知雷达脉冲积累过程中基于联合稀疏字典同步的目标距离走动补偿方法,以提高低信噪比压缩感知MIMO雷达的重构性能。主要工作如下:(1)研究了在脉冲体制下的MIMO雷达空时回波信号高维联合稀疏表示模型。通过分析空时回波信号三维数据块的切片方式,研究了空时回波信号多脉冲切片高维联合稀疏字典的三种构造方法,设计了一种稀疏性最优的联合稀疏表示模型。为MIMO雷达空时回波高维联合稀疏重构提供了基础。(2)针对单目标脉冲组间跨距离单元走动问题,提出了基于联合稀疏字典脉组对齐的目标距离走动补偿方法。通过对联合稀疏字典脉组对齐,矫正目标跨距离单元走动,在组内脉冲积累的基础上,实现脉冲组间积累。仿真实验验证,所提方法提高了跨距离单元走动下压缩感知雷达运动目标参数估计性能。(3)分别研究了空时高维联合稀疏字典构造,以及基于联合稀疏字典脉组对齐的目标距离走动补偿方法在集中式和分布式MIMO雷达的运动目标参数估计中的应用。设计了集中式和分布式MIMO雷达的空时高维联合稀疏表示模型和相应的联合稀疏字典脉组对齐方法,实现了低信噪比下集中式和分布式压缩感知MIMO雷达运动目标多参数联合估计。
[Abstract]:As a new type of radar, multi-input multi-output (MIMO) radar is confronted with the problems of massive data processing due to the increase of dimension compared with the traditional radar. The high sparsity of radar target relative to background provides the possibility for the application of compressed sensing technology. Radar signal processing based on compressed sensing technology has become a hot research area in radar field. Under the condition of low signal-to-noise ratio (SNR) detection, the reconstruction performance of compressed sensing will be greatly reduced or even invalidated, and the equidistant isomorphism of the sensing matrix makes it difficult to realize the pulse accumulation technique. In order to improve the signal-to-noise ratio (SNR) of multi-pulse information in compressed sensing MIMO radar, the combined sparse representation of space-time echo signal of MIMO radar based on compressed sensing is studied in this paper. In order to improve the reconstruction performance of compressed perceptual MIMO radar with low SNR, a compensation method for target range walk based on joint sparse dictionary synchronization in pulse accumulation process of compressed perceptual radar is proposed. The main work is as follows: (1) the high dimensional joint sparse representation model of MIMO radar space-time echo signal under pulse system is studied. By analyzing the slicing mode of three-dimensional data block of space-time echo signal, three methods of constructing multi-pulse slice of space-time echo signal with high dimension and sparsity dictionary are studied, and a sparsity optimal joint sparse representation model is designed. It provides the basis for MIMO radar space-time echo high-dimensional joint sparse reconstruction. (2) aiming at the problem of single target pulse group moving across the range unit, a new target range walk compensation method based on joint sparse dictionary pulse alignment is proposed. By aligning the combined sparse dictionary pulse groups, the correction target walks across the distance units, and the pulse accumulation is realized on the basis of the pulse accumulation within the group. Simulation results show that the proposed method improves the estimation performance of moving target parameters of compressed sensing radar under moving across range units. (3) Space-time high-dimensional combined sparse dictionary construction is studied respectively. And the application of target range walk compensation method based on joint sparse dictionary pulse group alignment to the motion target parameter estimation of centralized and distributed MIMO radar. The space-time high-dimensional joint sparse representation model of centralized and distributed MIMO radar and the corresponding joint sparse dictionary pulse alignment method are designed to realize the multi-parameter joint estimation of moving targets of centralized and distributed compressed MIMO radar at low SNR.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958
本文编号：2204905
[Abstract]:As a new type of radar, multi-input multi-output (MIMO) radar is confronted with the problems of massive data processing due to the increase of dimension compared with the traditional radar. The high sparsity of radar target relative to background provides the possibility for the application of compressed sensing technology. Radar signal processing based on compressed sensing technology has become a hot research area in radar field. Under the condition of low signal-to-noise ratio (SNR) detection, the reconstruction performance of compressed sensing will be greatly reduced or even invalidated, and the equidistant isomorphism of the sensing matrix makes it difficult to realize the pulse accumulation technique. In order to improve the signal-to-noise ratio (SNR) of multi-pulse information in compressed sensing MIMO radar, the combined sparse representation of space-time echo signal of MIMO radar based on compressed sensing is studied in this paper. In order to improve the reconstruction performance of compressed perceptual MIMO radar with low SNR, a compensation method for target range walk based on joint sparse dictionary synchronization in pulse accumulation process of compressed perceptual radar is proposed. The main work is as follows: (1) the high dimensional joint sparse representation model of MIMO radar space-time echo signal under pulse system is studied. By analyzing the slicing mode of three-dimensional data block of space-time echo signal, three methods of constructing multi-pulse slice of space-time echo signal with high dimension and sparsity dictionary are studied, and a sparsity optimal joint sparse representation model is designed. It provides the basis for MIMO radar space-time echo high-dimensional joint sparse reconstruction. (2) aiming at the problem of single target pulse group moving across the range unit, a new target range walk compensation method based on joint sparse dictionary pulse alignment is proposed. By aligning the combined sparse dictionary pulse groups, the correction target walks across the distance units, and the pulse accumulation is realized on the basis of the pulse accumulation within the group. Simulation results show that the proposed method improves the estimation performance of moving target parameters of compressed sensing radar under moving across range units. (3) Space-time high-dimensional combined sparse dictionary construction is studied respectively. And the application of target range walk compensation method based on joint sparse dictionary pulse group alignment to the motion target parameter estimation of centralized and distributed MIMO radar. The space-time high-dimensional joint sparse representation model of centralized and distributed MIMO radar and the corresponding joint sparse dictionary pulse alignment method are designed to realize the multi-parameter joint estimation of moving targets of centralized and distributed compressed MIMO radar at low SNR.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN958
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