计算机应用 ›› 2012, Vol. 32 ›› Issue (07): 2066-2069.DOI: 10.3724/SP.J.1087.2012.02066

• 典型应用 • 上一篇    下一篇

基于联合多目标概率密度模型的多目标检测前跟踪算法

樊玲1,2,张晓玲1   

  1. 1. 电子科技大学 电子工程学院,成都610054
    2. 乐山师范学院 物理与电子工程学院,四川 乐山614004
  • 收稿日期:2011-12-23 修回日期:2012-02-28 发布日期:2012-07-05 出版日期:2012-07-01
  • 通讯作者: 樊玲
  • 作者简介:樊玲(1977-),女,四川眉山人,讲师,博士研究生,主要研究方向:雷达微弱目标探测、雷达目标跟踪;张晓玲(1964-),女,四川成都人,教授,博士生导师,主要研究方向:合成孔径雷达处理、三维合成孔径雷达技术、逆合成孔径雷达技术、目标分类与识别、卫星导航定位。

Multi-target track-before-detect algorithm based on joint multi-target probability density model

FAN Ling1,2,ZHANG Xiao-ling1   

  1. 1. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 610054, China
    2. School of Physics and Electronic Engineering, Leshan Normal University, Leshan Sichuan 614004, China
  • Received:2011-12-23 Revised:2012-02-28 Online:2012-07-05 Published:2012-07-01
  • Contact: FAN Ling

摘要: 针对多目标环境下的检测前跟踪问题,提出了基于联合多目标概率密度(JMPD)模型的检测前跟踪(TBD)算法。JMPD模型同时模拟目标数目及其联合状态,采用粒子滤波递归估计JMPD实现目标数目及其状态的估计。仿真实验表明,所提算法在较小的延时检测的情况下,能准确估计目标的出生及消亡,并且航迹跟踪精确稳定,实现了对多个微弱目标的检测及跟踪。

关键词: 联合多目标概率密度, 多目标, 粒子滤波, 检测前跟踪

Abstract: Concerning the problem of Track-Before-Detect (TBD) in a multi-target environment, in this paper, a TBD algorithm based on Joint Multi-target Probability Density (JMPD) model was proposed. The JMPD was a single probabilistic entity that captured uncertainty about the number of targets present in the surveillance region as well as their individual states and a Particle Filter (PF) was used to recursively estimate the JMPD. The simulation results demonstrate that the birth and death of target can be estimated accurately as well as its trajectory by the proposed algorithm with smaller detection delays.

Key words: Joint Multi-Target Probability Density (JMPD), multi-target, Particle Filter (PF), Track-Before-Detect (TBD)

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