基于知识的海杂波背景下距离扩展目标检测  

Adaptive Detection of Range-spread Targets Based on Knowledge in Sea Clutter Background

作　　者：许述文[1,2] 薛健[1,2] 水鹏朗[1,2] XU Shuwen XUE Jian SHUI Penglang(National Key Laboratory of Radar Signal Processing, Xidian University, Xi＇an 710071, China Collaborative Innovation Center of Information Sensing and Understanding, Xi＇ an 710071, China)

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,西安710071 [2]西安电子科技大学信息感知技术协同创新中心,西安710071

出　　处：《电子与信息学报》2016年第12期3004-3010,共7页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61201296;61372136);中央高校基本科研业务费(JB160224);陕西省科协青年人才托举计划(20160205)~~

摘　　要：该文针对在辅助数据有限的情况下自适应检测器出现检测性能损失,提出基于杂波的先验知识分布的距离扩展目标自适应检测算法。复合高斯杂波的纹理和散斑的协方差矩阵分别被建模为服从逆伽玛分布的随机变量和逆复Wishart分布的随机矩阵。利用先验知识推导了纹理分量的最大后验估计,并结合广义似然比检验设计了不依赖辅助数据的距离扩展目标自适应检测器。仿真结果表明,提出的检测器在参数失配条件下具有好的鲁棒性,而且在辅助数据有限情况下检测性能优于传统的广义似然比检测器的检测性能。For the problem of detection performance loss of adaptive detectors on the condition that the secondary data are limited, the adaptive detection method of range-spread target based on the prior knowledge of clutter is proposed. The texture and the covariance matrix of speckle of clutter are respectively modeled as the random variable which follows the inverse Gamma distribution and the random matrix which follows the inverse complex Wishart distribution. Based on the prior knowledge, the MaximumA Posteriori（MAP） estimation of texture component is obtained and the adaptive detector of range spread target which does not need the secondary data is designed via utilizing the generalized likelihood ratio test. Finally, the detection performances of the proposed detector are evaluated and the experimental results illustrate that the proposed detector is robust in parameters mismatched situation and outperforms the conventional generalized likelihood ratio test detector for range-spread target in limited secondary data scenarios.

关 键 词：距离扩展目标 先验知识 复合高斯杂波 逆伽玛分布 逆复Wishart分布 

分 类 号：TN957.51[电子电信—信号与信息处理]