Robust mismatched filtering algorithm for passive bistatic radar using worst-case performance optimization

作     者：Gang CHEN Jun WANG Gang CHEN;Jun WANG

作者机构：National Laboratory of Radar Signal ProcessingXidian UniversityXi'an 710071China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2020年第21卷第7期

页      面：1074-1084页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：Project supported by the National Natural Science Foundation of China(No.61401526) the 111 Project China(No.B18039) the National Key Laboratory of Science Foundation of Science and Technology on Space Microwave,China(No.614241103030617) 

主　　题：Passive bistatic radar Range sidelobes Low signal-to-noise ratio Mismatched filtering Worst-case performance optimization 

摘      要：Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.