Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

查看全文 作　　者：ZHANG [1]Haowei;XIE [1]Junwei;GE [1]Jiaang;ZHANG [2]Zhaojian;LU [3]Wenlong

机构地区：[1]Air and Missile Defense College,Air Force Engineering University,Xi’an 710051,China;[2]Air Force Early Warning Academy of the PLA,Wuhan 410039,China;[3]Unit 95899 of the PLA,Beijing 100085,China

出　　处：《Journal of Systems Engineering and Electronics》索引2020年第31卷第2期,共13页

基　　金：supported by the National Natural Science Foundation of China(61601504)。 摘　　要：Due to the requirement of anti-interception and the limitation of processing capability of the fusion center, the subarray selection is very important for the distributed multiple-input multiple-output(MIMO) radar system, especially in the hostile environment. In such conditions, an efficient subarray selection strategy is proposed for MIMO radar performing tasks of target tracking and detection. The goal of the proposed strategy is to minimize the worst-case predicted posterior Cramer-Rao lower bound(PCRLB) while maximizing the detection probability for a certain region. It is shown that the subarray selection problem is NP-hard, and a modified particle swarm optimization(MPSO) algorithm is developed as the solution strategy. A large number of simulations verify that the MPSO can provide close performance to the exhaustive search(ES) algorithm. Furthermore, the MPSO has the advantages of simpler structure and lower computational complexity than the multi-start local search algorithm. 关键词：distributed MULTIPLE-INPUT multiple-output(MIMO)radar SUBARRAY selection TARGET tracking TARGET detection particle SWARM optimization(PSO)

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Finite sensor selection algorithm in distributed MIMO radar for joint target tracking and detection

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