高机动目标跟踪ATPM-IMM算法

doi:10.11959/j.issn.1000-436x.2022135

通信学报 ›› 2022, Vol. 43 ›› Issue (7): 93-101.doi: 10.11959/j.issn.1000-436x.2022135

高机动目标跟踪ATPM-IMM算法

曾浩¹, 母王强¹, 杨顺平²

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

修回日期:2022-06-14 出版日期:2022-07-25 发布日期:2022-06-01
作者简介:曾浩（1977- ），男，四川泸州人，博士，重庆大学教授、博士生导师，主要研究方向为阵列信号处理、无线通信技术
母王强（1997- ），男，重庆人，重庆大学硕士生，主要研究方向为目标跟踪
杨顺平（1976- ），男，四川岳池人，西南电子技术研究所高级工程师，主要研究方向为天线校准和天线测量技术
基金资助:
“十四五”国防预研基金资助项目(629010204)

High maneuvering target tracking ATPM-IMM algorithm

Hao ZENG¹, Wangqiang MU¹, Shunping YANG²

¹ School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
² Southwest Institute of Electronic Technology, Chengdu 610036, China

Revised:2022-06-14 Online:2022-07-25 Published:2022-06-01
Supported by:
National Defense Pre-Research Foundation of China during the “14th Five-Year Plan”(629010204)

摘要/Abstract

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%。

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

Abstract:

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 information of model posterior probability and transition probability matrix, it is suitable for both high and weak maneuvering target tracking.Simulation results demonstrate that the filtering accuracy of the proposed algorithm is improved about 11% compared with the existing algorithms.

Key words: maneuvering target tracking, interacting multiple model algorithm, adaptive transition probability, Bayes theorem

中图分类号:

TN953

曾浩, 母王强, 杨顺平. 高机动目标跟踪ATPM-IMM算法[J]. 通信学报, 2022, 43(7): 93-101.

Hao ZENG, Wangqiang MU, Shunping YANG. High maneuvering target tracking ATPM-IMM algorithm[J]. Journal on Communications, 2022, 43(7): 93-101.

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参考文献 19

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算法	乘法次数/次	加法次数/次
CIMM	14 241	11 829
文献[16]	15 024	12467
文献[18]	29 308	24 643
ATPM-IMM	26 839	22 506

算法	x方向/m	y方向/m	z方向/m	空间位置/m
CIMM	22.3	21.95	22.12	38.39
文献[16]	22	21.64	21.88	37.89
文献[18]	22.13	21.78	21.99	38.11
ATPM-IMM	18.46	17.67	21.65	33.6

算法	运行时间/μs
CIMM	203.3
文献[16]	214.2
文献[18]	421.2
ATPM-IMM	385.6

高机动目标跟踪ATPM-IMM算法

High maneuvering target tracking ATPM-IMM algorithm

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