未知探测概率的自适应多目标跟踪算法

doi:10.3969/j.issn.1000-3428.2017.08.050

计算机工程

未知探测概率的自适应多目标跟踪算法

刘晙¹,袁培燕²,邱昊³

(1.河南工学院计算机科学与技术系,河南新乡 453002;2.河南师范大学计算机与信息工程学院,河南新乡 453007; 3.91635部队,北京 102200)

收稿日期:2016-10-10 出版日期:2017-08-15 发布日期:2017-08-15
作者简介:刘晙(1981—),男,讲师、硕士,主研方向为算法分析、软件工程;袁培燕,副教授、博士;邱昊,工程师、博士。
基金资助:
国家自然科学基金(U1404602);国家高技术研究发展计划项目(2013AA01A215);河南省教育厅科学技术重点研究项目(14A520045)。

Adaptive Multi-target Tracking Algorithm with Unknown Detection Probability

LIU Jun¹,YUAN Peiyan²,QIU Hao³

(1.Department of Computer Science and Technology,Henan Institute of Technology,Xinxiang,Henan 453002,China; 2.College of Computer and Information Engineering,Henan Normal University,Xinxiang,Henan 453007,China; 3.Unit 91635 of PLA,Beijiing 102200,China)

Received:2016-10-10 Online:2017-08-15 Published:2017-08-15

摘要/Abstract

摘要： 为在复杂背景下对系统探测概率进行精确建模,提出一种适用于探测概率未知情形的多目标跟踪算法。通过时变自回归过程对探测概率进行建模,将参数化模型与标签多伯努利(LMB)滤波器相结合,并给出算法的序贯蒙特卡洛实现。仿真结果表明,所提算法的目标数和目标状态估计结果均优于Beta势平衡多目标多伯努利算法,平均最优次模型分配距离明显小于固定探测概率的LMB算法。

关键词: 多目标跟踪, 随机有限集, 标签多伯努利, 探测概率, 时变自回归

Abstract: In order to accurately model the system detection probability in a complex background,a Multi-Target Tracking(MTT) method with unknown detection probability is proposed.The detection probability is modeled by the Time Varying AutoRegressive(TVAR) process.The parameterized model is combined with the Labeled Multi-Bernoulli(LMB) filter,and the Sequential Monte Carlo(SMC) implementation of the proposed algorithm is given.Simulation results show that the target number and the target state estimation of the proposed algorithm are better than that of Beta Cardinality Balanced Multi-target Multi-Bernoulli(Beta-CBMeMBer),and the average Optimal Sub Pattern Assignment(OSPA) distance is significantly smaller than that of the LMB algorithm with fixed detection probability.

Key words: Multi-Target Tracking(MTT), Random Finite Set(RFS), Labeled Multi-Bernoulli(LMB), detection probability, Time Varying AutoRegressive(TVAR)

中图分类号:

TN953

刘晙,袁培燕,邱昊. 未知探测概率的自适应多目标跟踪算法[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2017.08.050.

LIU Jun,YUAN Peiyan,QIU Hao. Adaptive Multi-target Tracking Algorithm with Unknown Detection Probability[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2017.08.050.

http://www.ecice06.com/CN/Y2017/V43/I8/293

参考文献

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