• DocumentCode
    1794938
  • Title

    A navigation algorithm aided by multi-motion constraints of vehicle based on unified model

  • Author

    Xinxi Zhang ; Meifeng Guo ; Rong Zhang ; Luna Mi ; Mingliang Song ; Yongjian Zhang

  • Author_Institution
    Dept. of Precision Instrum., Tsinghua Univ., Beijing, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    749
  • Lastpage
    755
  • Abstract
    Precision of vehicle navigation can be significantly improved by adding motion constraints. How to model multi-motion constraints and choose appropriate motion constraint according to vehicle mobility need to be solved in practical usage. This article established a unified state error model and deduced a measurement model for several common vehicle motion constraints, like ZUPT, MCA and HDR, used the Kalman Filter and feedback correction. This article also proposed a mobility detection algorithm and a constraint control strategy to avoid the invalid motion constraints, the constraint control strategy could be adaptively applied according to the mobility. Simulation result stated that this algorithm could adaptively apply multi-motion constraints based on mobility detection. And, navigation precision was improved nearly two orders of magnitude except the heading angle. As the algorithm is simple and adaptive, it is of practical value in vehicle navigation.
  • Keywords
    Kalman filters; inertial navigation; motion control; road traffic control; road vehicles; HDR; Kalman filter; MCA; ZUPT; constraint control strategy; feedback correction; measurement model; mobility detection algorithm; multimotion constraint; navigation precision; unified state error model; vehicle mobility; vehicle motion constraint; vehicle navigation algorithm; Equations; Kalman filters; Mathematical model; Motion measurement; Navigation; Noise; Vehicles; HDR; Kalman Filter; MCA; Mobility Detection; ZUPT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4799-4700-3
  • Type

    conf

  • DOI
    10.1109/CGNCC.2014.7007305
  • Filename
    7007305