The initial alignment model of large misalignment angle is strong nonlinear, which means that the precision of nonlinear filter must be high. In order to make full use of the innovation, the error covariance matrix of fifth-order Cubature Kalman Filter (CKF) is scaled adaptively in this paper. The scaling factor can be obtained by calculating the ratio between matrix ranks of the current actual innovation and filtered innovation. The simulation experiments of large misalignment show that the improved algorithm has the higher accuracy and shorter convergence time than the traditional algorithm.


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    Title :

    Improved 5TH-CKF and its application in initial alignment


    Contributors:
    Wang, Wei (author) / Chen, Xiyuan (author)


    Publication date :

    2018-04-01


    Size :

    817029 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English