兰州理工大学学报 ›› 2025, Vol. 51 ›› Issue (1): 100-107.

• 自动化技术与计算机技术 • 上一篇    下一篇

基于非中心逆威沙特分布的非线性扩展目标跟踪方法

陈辉*1, 王秋菊1, 彭天曙2, 赵永红3   

  1. 1.兰州理工大学 电气工程与信息工程学院, 甘肃 兰州 730050;
    2.甘肃省计算中心,甘肃 兰州 730000;
    3.甘肃长风电子科技有限责任公司,甘肃 兰州 730070
  • 收稿日期:2022-07-19 出版日期:2025-02-28 发布日期:2025-03-03
  • 通讯作者: 陈辉(1978-),男,山西闻喜人,博士,教授,博导.Email:huich78@hotmail.com
  • 基金资助:
    国家自然科学基金 (62163023,61873116,62366031,62363023),甘肃省基础研究创新群体项目,2023年甘肃省军民融合发展专项项目,2024 年度甘肃省重点人才项目

A nonlinear extended target tracking method based on noncentral inverse Wishart distribution

CHEN Hui1, WANG Qiu-ju1, PENG Tian-shu2, ZHAO Yong-hong3   

  1. 1. College of Electrical and Information Engineering,Lanzhou University of Technology, Lanzhou 730050, China;
    2. Gansu Provincial Computing Center, Lanzhou 730000, China;
    3. Gansu Province Changfeng Electronic Technology Co. LTD., Lanzhou 730070, China
  • Received:2022-07-19 Online:2025-02-28 Published:2025-03-03

摘要: 针对非线性扩展目标跟踪问题,提出了在非中心逆威沙特分布条件下的非线性扩展目标跟踪方法.首先,在贝叶斯滤波框架下采用非中心逆威沙特分布进行算法的迭代,避免了因矩匹配或KL散度最小化而导致的信息丢失.其次,考虑到传统随机矩阵(RM)模型只能在线性观测条件下应用,利用去相关无偏转换量测将极坐标系下的非线性量测信息进行线性化处理,保证了量测转换的无偏性以及避免转换后的量测协方差估计与量测噪声的相关性,从而最终推导得到在非中心逆威沙特分布下非线性扩展目标跟踪的有效算法.椭圆形扩展目标的跟踪仿真实验验证了所提方法的有效性.

关键词: 扩展目标跟踪, 随机矩阵, 非中心逆威沙特分布, 非线性量测

Abstract: To solve the nonlinear extended target tracking problem, a nonlinear extended target tracking method is proposed under the condition of non-central inverse Wishart distribution. First, a non-central inverse Wishart distribution is used to the iterate algorithm under the framework of Bayesian filtering to avoid information loss caused by moment matching or KL divergence minimization. Then, recognizing the limitation of the traditional random matrix (RM) model, which is applicable only under linear observation conditions, the nonlinear measurement information in polar coordinate is linearized by using the de-correlation unbiased transformation algorithm, which ensures the unbiasedness of measurement transformation and avoids the correlation between the transformed measurement covariance estimation and the measurement noise. Furthermore, an effective algorithm for nonlinear extended target tracking based on non-central inverse Wishart distribution is derived. The effectiveness of the proposed method is verified by the tracking simulation of the elliptic extended target.

Key words: extended target tracking, random matrix, non-central inverse Wishart distribution, nonlinear measurement

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