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计算机工程 ›› 2009, Vol. 35 ›› Issue (12): 137-139. doi: 10.3969/j.issn.1000-3428.2009.12.048

• 人工智能及识别技术 • 上一篇    下一篇

贝叶斯目标跟踪方法的研究

郭晓松,李奕芃,郭君斌   

  1. (第二炮兵工程学院202教研室,西安 710025)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-06-20 发布日期:2009-06-20

Research on Bayesian Target Tracking Method

GUO Xiao-song, LI Yi-peng, GUO Jun-bin   

  1. (202 Staff Room, The Second Artillery Engineering College, Xi’an 710025)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-06-20 Published:2009-06-20

摘要: 针对贝叶斯滤波过程中存在的目标跟踪问题,提出几种典型的贝叶斯滤波方法,如EKF, UKF, PF和UPF等,基于这些方法所构建的框架,对它们进行性能测试和比较,并在非线性环境下,讨论这些方法的特点,仿真实验结果表明,在非线性非高斯环境下,UPF方法的性能是最优的。

关键词: 目标跟踪, 贝叶斯滤波, 非线性滤波方法

Abstract: Aiming at the problem of targe tracking in Bayesian filtering process, some typical Bayesian filtering methods such as EKF, UKF, PF and UPF are proposed. On basis of the frameworks set up by these methods, the performance of these methods are tested and compared, and the characteristics of them are discussed in non-linear environment. Simulation experimental results show that, in non-linear and non-Gaussian environment, the performance of UPF is the best.

Key words: target tracking, Bayesian filtering, non-linear filtering method

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