• DocumentCode
    1754828
  • Title

    PMI-Based Nonlinear H_\\infty Estimation of Unknown Sensor Error for INS/GPS Integrated System

  • Author

    Maiying Zhong ; Dingfei Guo ; Jia Guo

  • Author_Institution
    Sch. of Instrum. Sci. & Opto-Electron. Eng., Beihang Univ., Beijing, China
  • Volume
    15
  • Issue
    5
  • fYear
    2015
  • fDate
    42125
  • Firstpage
    2785
  • Lastpage
    2794
  • Abstract
    This paper deals with the problem of robust estimation for time-varying sensor errors of inertial navigation system (INS) and global positioning system integration. A nonlinear strapdown INS error model is established to describe the behavior of the the integrated system. Under assumptions of time-varying bias and noise being L2 norm bounded, a robust H nonlinear estimator by Krein space theory is proposed and, based on this, a proportional and multi-integral H estimator is developed for simultaneous estimation of the navigation states and sensor errors. Finally, a flight experiment is implemented to show the effectiveness of the proposed method.
  • Keywords
    Global Positioning System; Kalman filters; inertial navigation; nonlinear estimation; state estimation; Global Positioning System; INS-GPS integrated system; Kalman filtering; Krein space theory; L2 norm bounded; PMI-based nonlinear H estimation; inertial navigation system; multiintegral H estimator; navigation state estimation; nonlinear strapdown INS error model; proportional H estimator; robust time-varying sensor error estimation problem; time-varying bias; time-varying nois; unknown sensor error; Estimation; Global Positioning System; Noise; Sensor systems; Temperature sensors; Vectors; INS/GPS integrated system; PMI; Sensor error estimation; nonlinear ${H_infty }$ estimator; nonlinear H∞ estimator; sensor error estimation;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2014.2379719
  • Filename
    6983549