Journal of Systems Engineering and Electronics ›› 2011, Vol. 33 ›› Issue (11): 2546-2553.doi: 10.3969/j.issn.1001-506X.2011.11.38

• 软件、算法与仿真 • 上一篇    下一篇

迭代无味卡尔曼滤波器的算法实现与应用评价

程水英1,2, 余莉2   

  1. 1. 脉冲功率激光技术国家重点实验室, 安徽 合肥 230037; 2. 电子工程学院, 安徽 合肥 230037
  • 出版日期:2011-11-25 发布日期:2010-01-03

Algorithm realization and its application evaluation of the iterated unscented Kalman filter

CHENG Shui-ying1,2, YU Li2   

  1. 1. State Key Laboratory of Pulsed Power Laser Technology, Hefei 230037, China; 2. Electronic and Engineering Institute, Hefei 230037, China
  • Online:2011-11-25 Published:2010-01-03

摘要:

为了对各种迭代无味卡尔曼滤波(iterated unscented Kalman filter, IUKF)算法的应用及性能表现给出较为全面、客观的评价,分别导出并探讨了3种IUKF算法之间的内在联系。多种情况下的仿真应用表明,当观测噪声不太大,且该非线性系统状态的后验密度为可用高斯分布很好近似的单峰形式时,或者说是引起系统非线性的状态量是完全瞬时可观测时,选用恰当的IUKF算法,通过2~3次迭代,就可以在保持滤波一致性的条件下,进一步获得显著的精度收益;否则,IUKF相对于无味卡尔曼滤波(unscented Kalman filter, UKF)的迭代收益就难以保证。

Abstract:

To achieve a more comprehensive and objective judgment on the application and performance of various iterated unscented Kalman filter (IUKF), three versions of IUKF are derived and the implied internal relations are identified intrinsically too. The simulation results demonstrate that a proper IUKF algorithm may be applied with 2 or 3 iterations to achieve a prominent precision profit enjoying perfect filter consistency as well when the measurement noise is not too serious and the posterior density of the nonlinear system states with unimodal can be approximated perfectly by Gaussian function, in other words, when the state variables contributing to the system nonlinearity are full instantaneous observability; otherwise the iteration profits of the IUKF relative to the UKF are hard to be guaranteed.

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