电子学报 ›› 2019, Vol. 47 ›› Issue (12): 2457-2464.DOI: 10.3969/j.issn.0372-2112.2019.12.002

• 学术论文 • 上一篇    下一篇

初值自适应的磁性目标跟踪方法

戴忠华1, 周穗华1, 张宏欣2, 单珊1   

  1. 1. 海军工程大学兵器工程学院, 湖北武汉 430033;
    2. 解放军91439部队43分队, 辽宁大连 116041
  • 收稿日期:2018-12-14 修回日期:2019-06-19 出版日期:2019-12-25 发布日期:2019-12-25
  • 作者简介:戴忠华 男,1992年生于江西宁都.现为海军工程大学兵器工程学院博士研究生.主要研究方向为军用目标特性及其信息感知技术.E-mail:602024288@qq.com;周穗华 男,1962年出生,生广东五华人,1983年毕业于海军工程学院,2003年在海军工程大学获得博士学位,现为海军工程大学教授、博士生导师.从事军用目标特性信息处理及武器系统总体设计方面研究.
  • 基金资助:
    国家自然科学基金(No.51509252);国防预研项目(N0.41419010208)

Initial Value Adaptive Method for Magnetic Target Tracking

DAI Zhong-hua1, ZHOU Sui-hua1, ZHANG Hong-xin2, SHAN Shan1   

  1. 1. Department of Weaponry Engineering, Naval University of Engineering, Wuhan, Hubei 430033, China;
    2. Unit 43 of PLA Troop 91439, Dalian, Liaoning 116041, China
  • Received:2018-12-14 Revised:2019-06-19 Online:2019-12-25 Published:2019-12-25

摘要: 针对在初始先验信息缺失时磁性目标滤波跟踪方法发散问题进行研究,本文提出了一种多初值模型的解决框架,并以平方根形式的中心差分卡尔曼滤波器(Square-Root Central Difference Kalman Filter,SRCDKF)为例,结合多初值模型得到了SRCDKF自适应磁性目标跟踪算法.文章首先根据远距离磁偶极子的磁场等效性,建立了多初值滤波跟踪模型,然后基于最大似然选择理论推导了如何从多模型中选择最佳结果,即多初值模型的选择方法,最后以SRCDKF滤波器为滤波单元,得到了基于SRCDKF的自适应磁性目标跟踪算法.经过仿真试验表明:(1)多初值模型建立和选择方法的有效性;(2)基于SRCDKF的自适应磁性目标跟踪算法,在初始位置信息缺失的情况下,能够有效完成对磁性目标的跟踪;(3)以不同滤波器为滤波单元的自适应跟踪算法跟踪试验结果表明,多初值模型的解决框架可解决初值先验未知下的跟踪问题.

关键词: 磁性目标跟踪, 磁偶极子, 多初值模型, 最大似然选择, 自适应跟踪算法

Abstract: In order to solve the divergence of the magnetic target filter tracking method when the initial prior information is missing,this paper proposes a solution framework of multiple initial value models.Taking the square-root central difference Kalman filter(SRCDKF) as an example,the SRCDKF adaptive magnetic target tracking algorithm is obtained by combining multiple initial value models.Firstly,based on the magnetic field equivalence of long-distance magnetic dipoles,a multi-initial filter tracking model is established.Then based on the maximum likelihood selection theory,the method of how to choose the best result from multiple models is derived.Finally,using SRCDKF filter as the filtering unit,an adaptive magnetic target tracking algorithm based on SRCDKF is obtained.The simulation experiments show that:(1) the validity of the multi-initial model establishment and selection method;(2) the adaptive magnetic target tracking algorithm based on SRCDKF can effectively complete the tracking of magnetic targets in the absence of initial position information;(3) the tracking results of the adaptive tracking algorithm with different filters as the filtering unit show that the solution framework of the multi-initial value model can provide a method to solve the tracking problem under the initial value unknown.

Key words: magnetic target tracking, magnetic dipole, multiple initial value model, maximum likelihood selection, adaptive tracking algorithm

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