›› 2011, Vol. 31 ›› Issue (3): 14-19.doi: 10.3780/j.issn.1000-758X.2011.03.003

• 研究探讨 • 上一篇    下一篇

基于URTS平滑建议分布函数的PF算法设计及应用

李保利1,2, 宫轶松3, 归庆明4   

  1. (1信息工程大学测绘学院,郑州 450052)(2 中国卫星导航定位应用管理中心,北京 100088)(3 61618部队,北京 102102)(4 信息工程大学理学院,郑州 450001)
  • 收稿日期:2010-09-30 修回日期:2011-01-28 出版日期:2011-06-25 发布日期:2011-06-25
  • 作者简介:李保利 1972年生,2000年获解放军信息工程大学大地测量学与测量工程硕士学位,现为解放军信息工程大学大地测量学与测量工程博士研究生,工程师。主要从事误差理论、非线性滤波、智能优化算法及导航数据处理等方面的研究。
  • 基金资助:

    国家自然科学基金(40974009,10903032),中国卫星导航学术年会青年优秀论文

Design and Application of Particle Filtering Algorithm Based on URTS Smoothing Proposal Distribution Function

LI  Bao-Li1,2, GONG  Yi-Song3, GUI  Qing-Ming4   

  1. (1 Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450052)(2 China National Administration of GNSS and Applications, Beijing 100088)(3 Unit 61618,Beijing 102102)(4 Institute of Science, Information Engineering University, Zhengzhou 450001)
  • Received:2010-09-30 Revised:2011-01-28 Online:2011-06-25 Published:2011-06-25

摘要: 为改善基于Unscented Kalman滤波建议分布函数的粒子滤波状态估计的性能,将Unscented Kalman滤波与RTS(Rauch-Tung-Striebel)固定区间平滑算法融合,产生了一种新的建议分布函数——Unscented RTS平滑建议分布函数。该函数首先实施Unscented Kalman滤波,之后对此滤波结果进行RTS固定区间平滑,以此产生预测样本。以此新建议分布函数得到的预测粒子的精度较通常的以Unscented Kalman滤波方法作为建议分布函数时得到的预测粒子的精度将大为提高,进而提高相应的粒子滤波算法——PFURTS的状态估计精度。新算法的可行性和有效性在GPS/DR组合导航数据处理中得到了应用验证。

关键词: 粒子滤波, 建议分布函数, 航位推算, 全球定位系统

Abstract: To improve the state estimate performance of the particle filtering with the Unscented Kalman filtering proposal distribution function, the Unscented Kalman filtering and the Rauch-Tung-Striebel (RTS) fixed interval smoothing algorithm were integrated, and a new kind of proposal distribution function named as Unscented RTS smoothing proposal distribution function was designed. The Unscented RTS smoothing distribution implements the Unscented Kalman filtering, and then carries out the RTS fixedinterval smoothing to produce a prediction sample. The accuracy of prediction particles is greatly improved by the new proposal distribution function, and the state estimation accuracy of the corresponding particle filtering method (PF-URTS) is also improved. The applications of the new particle filtering algorithm to the GPS/DR integrated navigation system will prove the feasibility and validity of  the proposed  method.

Key words: Particle filtering, Proposal distribution function, Dead Reckoning, Global positioning systems