欢迎访问《兵工学报》官方网站,今天是 分享到:

兵工学报 ›› 2019, Vol. 40 ›› Issue (5): 1020-1029.doi: 10.3969/j.issn.1000-1093.2019.05.015

• 论文 • 上一篇    下一篇

基于迭代无偏有限冲击响应滤波的共轴跟踪技术研究

余潇, 柯芳, 袁佳, 高歆杨   

  1. (西南技术物理研究所, 四川 成都 610041)
  • 收稿日期:2018-10-18 修回日期:2018-10-18 上线日期:2019-07-26
  • 通讯作者: 柯芳(1968—), 女, 研究员, 博士, 硕士生导师 E-mail:nadya@sina.com
  • 作者简介:余潇(1994—), 男, 硕士研究生。 E-mail: novyuxiao@yeah.net

Research on On-axis Tracking Technology Based on Iterative UFIR Filter

YU Xiao, KE Fang, YUAN Jia, GAO Xingang   

  1. (Southwest Institute of Technical Physics, Chengdu 610041, Sichuan, China)
  • Received:2018-10-18 Revised:2018-10-18 Online:2019-07-26

摘要: 为了有效提升光电跟踪系统的跟踪精度,提出一种共轴跟踪改进方案。采用迭代无偏有限冲击响应(UFIR)滤波算法来替代传统卡尔曼滤波(KF)算法,进行系统状态估计与预测。迭代UFIR滤波算法由于不依赖噪声先验统计信息,可有效克服传统KF算法的不足,在噪声统计信息未知时能保持理想的预测精度,从而使改进后的系统在实际工况下仍能达到较高的跟踪精度。分别进行了迭代UFIR算法和KF算法对比的单元仿真实验,以及采用两种算法的共轴跟踪系统对比仿真实验,实验结果验证了理论分析的正确性,表明在噪声统计信息无法事先准确获得的实际工程应用中,基于迭代UFIR滤波的共轴跟踪改进方案较基于KF算法的传统方案鲁棒性更强,具有更大的应用潜力。

关键词: 光电跟踪系统, 共轴跟踪, 跟踪精度, 无偏有限冲击响应滤波器, 卡尔曼滤波

Abstract: An improved on-axis tracking scheme is proposed to effectively improve the tracking accuracy of photoelectric tracking system. The iterative unbiased finite impulse response (UFIR) filter algorithm is used to replace the traditional Kalman filter (KF) algorithm for state estimation and prediction. Because the iterative UFIR algorithm does not rely on the noise prior statistical information, it can overcome the shortcomings of the traditional KF algorithm and maintain the ideal prediction accuracy when the noise statistics are unknown, which makes the improved system also achieve the high tracking accuracy in actual operating condition. Two simulations were carried out,in which the KF was compared with the iterative UFIR filter, and two on-axis tracking systems which use above two algorithms were compared. Simulated results verify the correctness of the theoretical analysis, and show that the proposed scheme based on the iterative UFIR filter is more robust than the traditional KF-based scheme and has greater application potential in actual engineering where noise statistical information can't be accurately obtained in advance. Key

Key words: photoelectrictrackingsystem, on-axistracking, trackingaccuracy, unbiasedfiniteimpulseresponsefilter, Kalmanfilter

中图分类号: