• DocumentCode
    620008
  • Title

    State estimation with missing measurements using IMM

  • Author

    Shiyou Zheng ; Xiaofang Tang ; Meiqin Liu ; Senlin Zhang ; Weihua Sheng

  • Author_Institution
    Aviation Key Lab. of Sci. & Technol. on AISSS, Radar & avionics Inst. of AVIC, Wuxi, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    1868
  • Lastpage
    1873
  • Abstract
    The missing of the measurements will deteriorate the estimation or even make the estimators divergent. We first analyze the performance of the existed estimation approaches in nonlinear systems with missing measurements. According to the effectiveness of the multiple model estimation over single model estimation, we propose to give the estimates of the states using the interacting multiple model estimation (IMM). The IMM contains two model sets. One of them corresponds to the systems modes and the other corresponds to the occurrence of the missing of the measurements. The simulation results show the proposed approach is more stable and accurate than the existed estimation approaches.
  • Keywords
    measurement theory; nonlinear control systems; state estimation; IMM; interacting multiple model estimation; missing measurement; nonlinear system; state estimation; Educational institutions; Equations; Estimation; Mathematical model; Noise measurement; Nonlinear systems; Vectors; Gaussian Mixture; Interacting Multiple Model Estimation (IMM); Measurements Missing; Nonlinear System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561237
  • Filename
    6561237