导弹与制导技术

一种自适应的粒子局部 PHD 滤波

  • 童骞 ,
  • 李鸿艳 ,
  • 危璋 ,
  • 毛少锋 ,
  • 鹿传国
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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

童骞(1991-), 男, 湖南娄底人, 硕士研究生, 研究方向: 目标跟踪。

收稿日期: 2014-10-21

  网络出版日期: 2025-05-28

An Adaptive Particle Local PHD Filter

  • TONG Qian ,
  • LI HongYan ,
  • WEI Zhang ,
  • MAO Shaofeng ,
  • Lu Chuanguo
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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: 2014-10-21

  Online published: 2025-05-28

摘要

针对SMC-PHD滤波算法精度不高、计算量大的问题,提出一种自适应的粒子局部概率假设密度滤波算法。该算法首先利用加速度协方差自适应调整波门大小,划分目标区域与杂波区域,然后在各自区域分别进行粒子概率假设密度滤波,以达到提高滤波性能,减少计算量的目的。仿真结果表明,与SMC-PHD算法相比较,本算法提高滤波精度并减少了计算量。

本文引用格式

童骞 , 李鸿艳 , 危璋 , 毛少锋 , 鹿传国 . 一种自适应的粒子局部 PHD 滤波[J]. 弹箭与制导学报, 2015 , 35(5) : 25 -29 . DOI: 10.15892/j.cnki.djzdxb.2015.05.007

Abstract

Filter with standard particle probability assumption is of less accuracy and larger computation complexity. To solve the problem, an adaptive particle local PHD filter algorithm was proposed. The approach makes use of accelerate covariance to adjust adaptive gate, the size of which changes according to target movement condition. The object region and clutter region are separated, part of clutter eliminated, and particle PHD filter is performed in each region separately, with simulation at last. The simulation reveals that compared with standard PHD filter, the amount of calculation is reduced while the precision increases.

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