CLEAN-based air moving target detection for the SFM radar-communication system

作     者：Wang, Zhaofeng Liao, Guisheng Yang, Zhiwei Ji, Yuxin 

作者机构：Xidian Univ Natl Lab Radar Signal Proc 2 South Taibai Rd Xian Shaanxi Peoples R China Shanghai Univ 99 Shangda Rd Shanghai Peoples R China 

出 版 物：《IET SIGNAL PROCESSING》 (IET Signal Proc.)

年 卷 期：2019年第13卷第2期

页      面：199-206页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：National Key Research and Development Program of China [2016YFE0200400] National Natural Science Foundation of China (NSFC) 

主　　题：autocorrelation function object detection SFM-based integrated system iterative methods multifunction radar sparse representation method complex reflection coefficient iterative cancellation SFM radar-communication system undesired sidelobes signal representation radar signal processing transmitting signal modulation ACF communication function space-frequency modulation signal CLEAN-based air moving target detection correlation methods 

摘      要：Space-frequency modulation (SFM) signal is a potential waveform for multifunction radar with high degrees of freedom of space, time, and frequency. However, the introduction of the additional communication function will modulate the transmitting signal, which will severely deteriorate the autocorrelation function (ACF). Here, a modified CLEAN method is proposed to eliminate the influence of undesired sidelobes in ACF on the air target detection. In the proposed method, undesired sidelobes are treated as extra features of real target to obtain more precise estimation of its complex reflection coefficient. Moreover, by considering about the sparsity of air targets, the authors employ the sparse representation method to estimate the response of the current strongest target. Then the target occlusion is eliminated by iterative cancellation. Simulation results demonstrate that the proposed detector is reliable and effective for the SFM-based integrated system.