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.


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    Title :

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


    Contributors:
    Zhang, Xinxi (author) / Guo, Meifeng (author) / Zhang, Rong (author) / Mi, Luna (author) / Song, Mingliang (author) / Zhang, Yongjian (author)


    Publication date :

    2014-08-01


    Size :

    249184 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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