J4 ›› 2010, Vol. 37 ›› Issue (6): 1042-1047.doi: 10.3969/j.issn.1001-2400.2010.06.011

• 研究论文 • 上一篇    下一篇



  1. (西安电子科技大学 电子工程学院,陕西 西安  710071)
  • 收稿日期:2009-12-22 出版日期:2010-12-20 发布日期:2011-01-22
  • 通讯作者: 郭辉
  • 作者简介:郭辉(1985-),男,西安电子科技大学博士研究生,E-mail: ghui_xd@yahoo.cn.
  • 基金资助:


Quasi-Monte-Carlo Gaussian particle filter based target tracking for the multiple passive sensor

GUO Hui;JI Hong-bing;WU Bin   

  1. (School of Electronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2009-12-22 Online:2010-12-20 Published:2011-01-22
  • Contact: GUO Hui



关键词: 多传感器, 拟蒙特卡罗-高斯粒子滤波器, 目标跟踪


This paper employs Quasi-Monte-Carlo (QMC) sampling to replace conventional Monte-Carlo (MC) sampling, thus improving the performance of the Gaussian Particle Filter (GPF). A multi-passive-sensor target tracking algorithm based on the Quasi-Monte-Carlo Gaussian Particle Filter (QMC-GPF) is proposed in connection with the multi-sensor centralized fusion strategy, which resolves the strong nonlinearity and weak observability problem in a multi-passive-sensor tracking system more efficiently. The algorithm not only reduces the computational complexity, but also improves the accuracy and stability of the tracking algorithm, thus getting fast convergence. Moreover, because of the parallel structure, which makes it easier to realize with large-scale integrated circuits.

Key words: passive sensors, Quasi-Monte-Carlo Gaussian particle filter, target tracking