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弹箭与制导学报 >

2015 , Vol. 35 >Issue 2: 25 - 28

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2015.02.007

导弹与制导技术

基于迭代积分粒子滤波的目标跟踪算法

  • 毛少锋 ,
  • 冯新喜 ,
  • 鹿传国 ,
  • 危璋
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  • 1 空军工程大学信息与导航学院, 西安 710077
    2 95806部队, 北京 100000

毛少锋(1989-),男,陕西澄城人,硕士研究生,研究方向:目标跟踪。

收稿日期: 2014-03-25

  网络出版日期: 2025-05-26

基金资助

陕西省自然科学基金(2011JM8023)

收起

Target Tracking Algorithm Based on Iterative Quadrature Particle Filter

  • MAO Shaofeng ,
  • FENG Xinxi ,
  • LU Chuanguo ,
  • WEI Zhang
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  • 1 Information and Navigation College, Air Force Engineering University, Xi'an 710077, China
    2 No. 95806 Unit, Beijing 100000, China

Received date: 2014-03-25

  Online published: 2025-05-26

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摘要

针对粒子滤波在非线性目标跟踪中存在粒子退化的问题,提出一种迭代积分粒子滤波的目标跟踪算法。该算法从改进重要性函数的角度入手,在积分卡尔曼滤波的基础上,通过高斯牛顿迭代的方法进行量测更新,并对粒子集合中的粒子进行迭代积分卡尔曼滤波,使得构造的重要性函数更加贴近真实后验分布。仿真结果表明,与粒子滤波算法、积分粒子滤波算法相比,该算法在有效改善非线性目标跟踪中粒子退化的同时,提高了跟踪精度。

关键词： 高斯牛顿迭代; 积分卡尔曼滤波; 重要性函数; 非线性目标跟踪

本文引用格式

毛少锋 , 冯新喜 , 鹿传国 , 危璋 . 基于迭代积分粒子滤波的目标跟踪算法[J]. 弹箭与制导学报, 2015 , 35(2) : 25 -28 . DOI: 10.15892/j.cnki.djzdxb.2015.02.007

Abstract

In view of particle degradation problem of nonlinear target tracking, an iterative Quadrature particle filter (IQPF) target tracking algorithm was proposed based on the improved importance function. The algorithm is the basis of the Quadrature Kalman filter (QKF), the Gauss-Newton iteration method is used to make iterative processing, which can take the measurement into account by means of the iterative Quadrature Kalman filter, to make the importance function be closer to the true posterior. The computer simulation results indicate that compared with the particle filter (PF) algorithm and the Quadrature particle filter (QPF) algorithm, this algorithm has better performance in accuracy and effectively solves the particle degradation problem in nonlinear tracking.

Key words： Gauss-Newton iteration; Quadrature Kalman filter; importance function; nonlinear tracking problem

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