J4 ›› 2010, Vol. 37 ›› Issue (6): 1048-1052.doi: 10.3969/j.issn.1001-2400.2010.06.012

• 研究论文 • 上一篇    下一篇

两种外辐射源雷达跟踪算法性能分析

李红伟;王俊;刘玉春   

  1. (西安电子科技大学 雷达信号处理国家重点实验室,陕西 西安  710071)
  • 收稿日期:2009-11-10 出版日期:2010-12-20 发布日期:2011-01-22
  • 通讯作者: 李红伟
  • 作者简介:李红伟(1983-),男,西安电子科技大学博士研究生.E-mail: hwli@mail.xidian.edu.cn.
  • 基金资助:

    国家部委重点基金资助项目(9140A07050908DZ0103);教育部创新团队计划资助项目

Performance analysis of two passive radar tracking algorithms

LI Hong-wei;WANG Jun;LIU Yu-chun   

  1. (National Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2009-11-10 Online:2010-12-20 Published:2011-01-22
  • Contact: LI Hong-wei

摘要:

针对以调频广播电台为辐射源的无源雷达跟踪精度较低的问题,将到达时间定位方法分别与扩展卡尔曼滤波和粒子滤波算法结合来提高跟踪精度.分析了高斯噪声环境、闪烁噪声环境及雷达布站方式对两种算法跟踪精度的影响,并比较了两种算法的运算时间.仿真和实测数据表明:粒子滤波算法更适合于闪烁噪声环境下的跟踪,而扩展卡尔曼滤波能满足实时处理的要求.另外,合理的雷达布站方式可进一步提高无源跟踪精度.

关键词: 外辐射源雷达, 扩展卡尔曼滤波, 粒子滤波, 跟踪性能

Abstract:

Since the passive radar based on the FM radio station has a low tracking precision, this paper proposes that the time of arrival(TOA) location method be combined with the Extended Kalman Filter(EKF) and Particle Filter(PF) respectively to improve passive tracking performance. Tracking performance of the two algorithms and their calculation time are studied, and factors that affect the tracking precision including glint noise and site-deploying are also discussed. Simulation results and real data show that the PF is more adaptive to glint noise environment. Nevertheless, the EKF can satisfy real time processing. Moreover, a reasonable site-deploying scheme will further provide a better tracking precision.

Key words: passive radar, extended Kalman filter, particle filter, tracking performance