Multiple model efficient particle filter based track-before-detect for maneuvering weak targets  

作　　者：BAO Zhichao JIANG Qiuxi LIU Fangzheng 

机构地区：[1]College of Electronic and Engineering,National University of Defense and Technology,Hefei 230037,China

出　　处：《Journal of Systems Engineering and Electronics》2020年第4期647-656,共10页系统工程与电子技术（英文版）

基　　金：supported by the Natural Science Foundation of Anhui Province(1708085QF149)。

摘　　要：It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.

关 键 词：particle filter track-before-detect(TBD) maneuvering target tracking multiple model(MM) 

分 类 号：TN713[电子电信—电路与系统]