基于EKF及弹道方程的弹道目标跟踪滤波器设计

doi:10.12305/j.issn.1001-506X.2022.10.25

摘要/Abstract

摘要：

针对地面跟踪雷达多目标、低数据率、高跟踪精度要求, 提出了基于弹道运动方程的扩展卡尔曼滤波(extended Kalman filter, EKF)算法。建立了导弹被动段精确的质心运动方程, 改进了EKF算法, 经过与传统的基于常加速模型的EKF算法和基于弹道运动方程的无迹卡尔曼滤波(unscented Kalman filter, UKF)算法比较, 验证了基于弹道运动方程的EKF具有低数据率下滤波精度高、计算量小等优点, 解决了地面跟踪雷达实际中遇到的问题。

关键词: 弹道目标, 质心运动方程, 扩展卡尔曼滤波, 滤波方法

Abstract:

Given the requirement of more targets, lower track rate, higher track precision of radar, an extended Kalman filter (EKF) algorithm based on ballistic equation is proposed. Centroid motion equation of ballistic missile in midcourse and reentry is established, and EKF algorithm is improved. Through comparing to conventional EKF algorithm based on constant acceleration model and unscented Kalman filter (UKF) algorithm based on ballistic motion equation, EKF algorithm based on ballistic equation has higher filter precision, faster computation speed, which solves the practical problems in radar.

Key words: ballistic target, mass center motion equation, extended Kalman filter (EKF), filtering method

中图分类号:

TN953

孙照强, 王志贵, 孟飞, 李陆雨, 于中, 陈燕. 基于EKF及弹道方程的弹道目标跟踪滤波器设计[J]. 系统工程与电子技术, 2022, 44(10): 3207-3212.

Zhaoqiang SUN, Zhigui WANG, Fei MENG, Luyu LI, Zhong YU, Yan CHEN. Ballistic target tracking filter design based on EKF and ballistic equations[J]. Systems Engineering and Electronics, 2022, 44(10): 3207-3212.

图/表 8

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