基于IMM-UKF-CS的混合环境目标跟踪

doi:10.16182/j.issn1004731x.joss.201701007

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (1): 43-48.doi: 10.16182/j.issn1004731x.joss.201701007

基于IMM-UKF-CS的混合环境目标跟踪

周彦^1,2, 胡岚^1,2, 王冬丽¹

1.湘潭大学信息工程学院,湖南湘潭 411105;
2.湘潭大学控制工程研究所,湖南湘潭 411105

收稿日期:2015-04-27 修回日期:2015-07-29 出版日期:2017-01-08 发布日期:2020-06-01
作者简介:周彦(1978-),男,湖南邵阳,博士,副教授,研究方向为智能决策与信息融合;胡岚(1990-),女,湖南吉首,硕士生,研究方向为智能信息处理。
基金资助:
国家自然科学基金(61104210, 61100140)

Target Tracking in Hybrid Environment Based on IMM-UKF-CS

Zhou Yan^1,2, Hu Lan^1,2, Wang Dongli¹

1. College of Information Engineering, Xiangtan University, Xiangtan 411105, China;
2. Institute of Control Engineering, Xiangtan University, Xiangtan 411105, China

Received:2015-04-27 Revised:2015-07-29 Online:2017-01-08 Published:2020-06-01

摘要/Abstract

摘要： 针对视距(Line of Sight,LOS)和非视距(None-Line of Sight,NLOS)混合环境机动目标跟踪问题,提出一种基于“当前”统计模型(current statistical, CS)和无迹卡尔曼滤波(unscented Kalman filter, UKF)的交互式多模型方法(IMM-UKF-CS)。该方法在交互式多模型的框架内,利用CS在机动目标跟踪方面的优势,并选择具有较高跟踪精度且计算代价较低的UKF作为子滤波器。仿真结果表明：在LOS/NLOS混合环境中,IMM-UKF-CS具有较高的跟踪精度、较强的鲁棒性及较低的时间代价,具有良好的应用价值。

关键词: 机动目标跟踪, LOS/NLOS混合环境, “当前”统计模型, 无迹卡尔曼滤波, 交互式多模型

Abstract: To attack the maneuvering target tracking problem in LOS/NLOS hybrid environments, an interacting multiple model (IMM) tracking algorithm based on "current" statistical (CS) model and unscented Kalman filter (UKF) was proposed (IMM-UKF-CS). In the framework of IMM, it took advantage of CS in maneuvering target tracking and chose UKF as the sub-filter for the high positioning accuracy and low computational cost. Simulation results show that IMM-UKF-CS possesses higher tracking accuracy, better robustness and lower time cost, which promises for maneuver target tracking in LOS/NLOS hybrid environments.

Key words: maneuvering target tracking, LOS/NLOS hybrid environment, current statistic model, UKF, interacting multiple model

中图分类号:

TP391

周彦, 胡岚, 王冬丽. 基于IMM-UKF-CS的混合环境目标跟踪[J]. 系统仿真学报, 2017, 29(1): 43-48.

Zhou Yan, Hu Lan, Wang Dongli. Target Tracking in Hybrid Environment Based on IMM-UKF-CS[J]. Journal of System Simulation, 2017, 29(1): 43-48.

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基于IMM-UKF-CS的混合环境目标跟踪

Target Tracking in Hybrid Environment Based on IMM-UKF-CS

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