高机动目标跟踪ATPM-IMM算法  

High maneuvering target tracking ATPM-IMM algorithm

作　　者：曾浩[1] 母王强 杨顺平[2] ZENG Hao;MU Wangqiang;YANG Shunping(School of Microelectronics and Communication Engineering,Chongqing University,Chongqing 400044,China;Southwest Institute of Electronic Technology,Chengdu 610036,China)

机构地区：[1]重庆大学微电子与通信工程学院,重庆400044 [2]西南电子技术研究所,四川成都610036

出　　处：《通信学报》2022年第7期93-101,共9页Journal on Communications

基　　金：“十四五”国防预研基金资助项目(No.629010204)。

摘　　要：在高机动目标跟踪中,针对标准交互式多模型算法使用固定的转移概率矩阵导致跟踪精度下降的问题,提出了一种转移概率矩阵具备自适应更新的高机动目标跟踪ATPM-IMM算法。所提算法对模型后验概率和转移概率矩阵的先验信息要求不高,既适用于高机动目标跟踪,也适用于弱机动目标跟踪。仿真结果表明,所提算法的滤波精度比现有算法提升了约11%。For high maneuvering target tracking,the accuracy of tracking will degrade in common IMM algorithm due to the fixed transition probability matrix.Therefore,a new ATPM-IMM algorithm for high maneuvering target tracking was proposed,which could update the transition probability matrix adaptively.The proposed algorithm requires less prior in-formation of model posterior probability and transition probability matrix,it is suitable for both high and weak maneu-vering target tracking.Simulation results demonstrate that the filtering accuracy of the proposed algorithm is improved about 11%compared with the existing algorithms.

关 键 词：机动目标跟踪 交互式多模型算法 自适应转移概率 贝叶斯定理 

分 类 号：TN953[电子电信—信号与信息处理]