现代防御技术 ›› 2022, Vol. 50 ›› Issue (1): 67-73.DOI: 10.3969/j.issn.1009-086x.2022.01.010

• 目标特性与探测跟踪技术 • 上一篇    下一篇

弹道目标跟踪滤波方法研究

孙照强1, 魏巍2, 王志贵1, 陈燕1   

  1. 1.北京无线电测量研究所,北京 100854
    2.中国卫星导航系统管理办公室,北京 100053
  • 收稿日期:2021-06-10 修回日期:2021-09-15 出版日期:2022-02-28 发布日期:2022-02-23
  • 作者简介:孙照强(1981-),男,山东菏泽人。研究员,硕士,主要从事雷达总体,信号及数据处理、目标识别。

Research on Tracking and Filtering Method of Ballistic Target

Zhao-qiang SUN1, Wei WEI2, Zhi-gui WANG1, Yan CHEN1   

  1. 1.Beijing Institute of Radio Measurement, Beijing 100854, China
    2.China Satellite Navigation System Management Office, Beijing 100053, China
  • Received:2021-06-10 Revised:2021-09-15 Online:2022-02-28 Published:2022-02-23

摘要:

主要对弹道目标的跟踪滤波方法进行了综述,对扩展卡尔曼滤波(extended Kalman filter, EKF)、转换测量卡尔曼滤波(conversion measurement Kalman filter, CMKF)、基于弹道运动方程的扩展卡尔曼滤波(ballistic extended Kalman filter, BEKF)、基于弹道运动方程的无敏卡尔曼滤波(ballistic unscented Kalman filter, BUKF)4种滤波算法的关键点、优缺点进行了剖析。进一步利用仿真的弹道数据对4种滤波方法的效能进行了验证,对比了不同滤波器的滤波精度和再入目标的跟踪性能,分析了质阻比对滤波性能的影响,提出了选择和设计目标跟踪滤波方法时需要考虑的几个问题,为雷达滤波方法的选择和设计提供参考和依据。

关键词: 弹道目标, 跟踪, 扩展卡尔曼滤波, 转换测量卡尔曼滤波, 无敏卡尔曼滤波, 滤波器设计

Abstract:

The method of tracking filter of ballistic target is summarized. The key points, advantages and disadvantages of the extended Kalman filter (EKF), conversion measurement Kalman filter (CMKF), ballistic EKF (BEKF), and ballistic unscented Kalman filter (BUKF) are analyzed. The efficacy of the four filtering methods is further verified using simulated ballistic data. The filtering precision, tracking performance of different filters for reentry target are compared and the effect of ballistic coefficient and measure error on filter performance is analyzed. The method of forming covariance of measure error is proposed, which improves adaptability and precision of filter. Several problems that should be considered when choosing and designing target tracking filter methods are proposed to provide reference and bases for the selection and desing of radar filtering methods.

Key words: ballistic target, tracking, extended Kalman filter, conversion measurement Kalman filter, unscented Kalman filter, filter design

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