K-分布杂波下利用方位参考单元的最优自适应检测方法

发布时间：2018-03-11 03:14

本文选题：海杂波　切入点：运动目标检测　出处：《西安电子科技大学》2015年硕士论文　论文类型：学位论文

【摘要】：海杂波背景下的动目标检测尤其对弱小目标检测的研究在军用和民用领域都具有非常重要的意义,同时也是雷达目标检测领域的一大难题。本文通过对海杂波背景下的目标检测技术详细研究,提出了一种基于载机相参雷达扫描回波数据进行多普勒补偿的相参自适应最优检测方案。其主要优势是在进行空间多普勒补偿后,将已检测过的相邻波位数据作为先验信息,充分利用到当前分辨单元的目标检测中。首先,分析了海杂波的物理组成机理和统计特性。在物理组成机理方面,主要介绍了海杂波的后向散射机理以及三分量模型;在统计特性方面,讨论了海杂波的幅度特性和相关特性。海杂波特性的研究和建模,为目标检测算法设计和性能提升提供了前提条件和理论支撑。其次,回顾了海杂波背景下的非相干累积检测方法和自适应检测方法,并分析了检测方法的适用范围以及其优缺点。相干累积检测方法主要包括均值类CFAR检测算法、有序统计量类CFAR检测算法和删除单元平均的CFAR检测算法;而自适应检测方法介绍了广义似然比检测算法、自适应匹配滤波检测算法和自适应归一化匹配滤波检测算法。本文在这些检测算法的研究基础上,进一步研究寻找应用范围更为广泛的检测器。最后,为了整个空间多普勒补偿的相参自适应最优检测方案的框架完整,介绍了海杂波的K-分布模型和α-AMF自适应检测器。该检测器是K-分布下广泛适应于高斯杂波背景以及非高斯杂波背景下的近似最优检测器。由于自适应检测器高度依赖于对杂波背景估计的协方差矩阵,给出了三种稳健的杂波协方差矩阵估计方法。随后,提出了基于机载波束扫描条件下空间多普勒补偿的最优自适应检测方案。该方案在进行多普勒补偿条件后,合理利用了已检测过的相邻波位参考单元回波数据,将之作为先验信息,用于当前待检测单元的目标检测中。而且,为了消除雷达回波数据不同波位间由于载机运动引起的多普勒效应,提出了分辨单元载机多普勒补偿量估计方法。仿真数据和实测海杂波数据实验证实了提出方案的有效性并且与传统只考虑距离维选取参考单元的检测方案相比有明显的性能改善。
[Abstract]:The research of moving target detection under sea clutter background, especially for small and weak target detection, is of great significance in both military and civil fields. At the same time, it is also a difficult problem in the field of radar target detection. In this paper, a coherent adaptive optimal detection scheme based on the scan echo data of aircraft coherent radar is proposed. The main advantage of the scheme is that after the spatial Doppler compensation, the detected adjacent wave position data are regarded as prior information. Firstly, the physical composition and statistical characteristics of sea clutter are analyzed. In terms of physical composition mechanism, the backscattering mechanism and three-component model of sea clutter are introduced. In terms of statistical characteristics, the amplitude and correlation characteristics of sea clutter are discussed. The research and modeling of sea clutter characteristics provide a prerequisite and theoretical support for the design of target detection algorithm and performance improvement. In this paper, the incoherent cumulant detection method and adaptive detection method in sea clutter background are reviewed, and the applicable range of the detection method and its advantages and disadvantages are analyzed. The coherent cumulative detection method mainly includes the mean class CFAR detection algorithm. The CFAR detection algorithm of ordered statistics and the CFAR detection algorithm of deleting unit average, while the generalized likelihood ratio detection algorithm is introduced in the adaptive detection method. Adaptive matched filter detection algorithm and adaptive normalized matched filter detection algorithm. Based on the research of these detection algorithms, this paper further studies the search for a more widely used detector. Finally, In order to complete the frame of the coherent adaptive optimal detection scheme for the whole spatial Doppler compensation, This paper introduces the K- distribution model of sea clutter and the 伪 -AMF adaptive detector, which is an approximate optimal detector for Gao Si clutter background and non-#china_person1# clutter background under K- distribution. The covariance matrix depends on the background estimation of clutter. Three robust estimation methods of clutter covariance matrix are presented. Then, an optimal adaptive detection scheme based on airborne beam scanning is proposed. The echo data of the detected adjacent wave position reference unit is reasonably used as a priori information for the target detection of the current detection unit. In order to eliminate the Doppler effect caused by the motion of the carrier between different wave levels of radar echo data, In this paper, a method of Doppler compensation estimation based on resolution unit is proposed. The simulation data and the measured sea clutter data show that the proposed scheme is effective and compared with the traditional detection scheme, which only takes into account the distance dimension of the reference unit. Significant performance improvements.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN959

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