非均匀环境下基于知识辅助的扩展目标Wald检测器  

Knowledge-Aided Wald Detector for Range-Extended Target in Nonhomogeneous Environments

作　　者：王楠 孙进平[1] 王文光[1] WANG Nan;SUN Jin-ping;WANG Wen-guang(Institute of Electronic and Information Engineering,Beihang University,Beijing 100191,China)

机构地区：[1]北京航空航天大学电子信息工程学院,北京100191

出　　处：《信号处理》2018年第6期714-721,共8页Journal of Signal Processing

基　　金：国家自然科学基金(61471019)

摘　　要：针对分布式多输入多输出(Multiple Input Multiple Output,MIMO)雷达中运动扩展目标的检测问题,本文首先假设每个发射-接收天线组的干扰信号协方差矩阵为互不相同的随机矩阵,以模拟实际的非均匀工作环境。然后引入知识辅助模型,建立先验信息矩阵,描述非均匀环境下的干扰信号特性,其中所有发射-接收天线组的干扰协方差矩阵服从以先验信息矩阵为基础的逆Wishart分布。在此基础上,设计了一种基于知识辅助的Wald(KA-Wald)检测器。仿真实验表明,在小样本的情况下,本文设计的KA-Wald检测器在检测性能上优于传统Wald检测器。而与已有的基于知识辅助的广义似然比检验(KA-GLRT)检测器相比,检测性能相近,但是计算效率更高。This paper deals with the problem of detecting the moving range-extended target in the distributed MIMO radar.Firstly,the interference covariance matrices corresponding to different transmit-receive（ Tx-Rx） antennas are modeled as random matrices which express nonhomogeneous environments. Then a knowledge-aided model which makes these random matrices share a prior covariance matrix structure is built to simulate the characteristics of clutter and noise in nonhomogeneous environments. On this basis,we design a new knowledge-aided Wald（ KA-Wald） detector. Simulation results show that the proposed detector possesses a better detection performance compared with the traditional Wald detector. And relative to the knowledge-aided generalized likelihood ratio test（ KA-GLRT） detector,the proposed KA-Wald detector has a similar detection performance but a higher efficiency.

关 键 词：分布式多输入多输出雷达 知识辅助 非均匀环境 扩展目标 

分 类 号：TN953[电子电信—信号与信息处理]