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  • 标题:An Improved Strong Tracking UKF Based on Fading Factor
  • 本地全文:下载
  • 作者:Jian Feng ; Xiao-dong Su ; Yu-ru Zhang
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2014
  • 卷号:7
  • 期号:4
  • 页码:1-10
  • DOI:10.14257/ijhit.2014.7.4.01
  • 出版社:SERSC
  • 摘要:STUKF (Strong tracking UKF) algorithm uses the time-varying fading factor to fade the past data and reduce the impact on current filter value, thus achieves the goal of adjusting the filter gain matrix in real time. But STUKF algorithm needs three UT for each filtering, and compared with the UKF filter, calculating amount of three UT increases seriously, and it is not conducive to application of engineering, therefore this paper presents an improved STUKF algorithm. Compared with the traditional STUKF filter, this new algorithm introduces the formulas of redefined fading factor. By changing the position of the fading factor, it improves the accuracy and robustness of the algorithm and reduces the computational complexity of the algorithm. Finally simulation results show that the new algorithm has higher precision and stronger robustness.
  • 关键词:UKF; Strong Ttracking; Kalman Filter; Fading Factor; GPS; D/R
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