双层无迹卡尔曼滤波

Feng Yang, Li Tao Zheng, Jia Qi Wang, Quan Pan

科研成果: 期刊稿件文章同行评审

29 引用 (Scopus)

摘要

The unscented Kalman filter (UKF) has the problem of the inaccurate estimation in strong nonlinear systems. To solve this problem, the double layer unscented Kalman filter (DLUKF) algorithm is proposed. In the proposed algorithm, the weighted sampling points are used to represent the prior distribution, and then the inner layer UKF algorithm is used to update each sampling point. Finally, the state estimations are obtained by the update mechanism of the outer layer UKF algorithm. Simulation results show that the proposed algorithm not only has a low computational complexity, but also has a very good estimation accuracy, compared with the existing filtering algorithms.

投稿的翻译标题Double Layer Unscented Kalman Filter
源语言繁体中文
页(从-至)1386-1391
页数6
期刊Zidonghua Xuebao/Acta Automatica Sinica
45
7
DOI
出版状态已出版 - 7月 2019

关键词

  • Improved unscented Kalman filters
  • Sampling strategy
  • State estimation
  • Unscented Kalman filter (UKF)
  • Unscented particle filter (UPF)

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