An improved adaptive variational Bayesian (VB) nonlinear filter is proposed. Through Cubature sampling, inverse Wishart distribution is introduced to jointly estimate system states and inaccurate measurement noise for nonlinear systems. Furthermore, to avoid non-positive definite problem of the state covariance matrix in joint estimation, Singular Value Decomposition (SVD) is introduced to VBCKF, based on which SVD-VBCKF is designed. Besides, computational complexity of proposed filter is analyzed theoretically. Simulation results demonstrate that proposed SVD-VBCKF has higher filtering accuracy.


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    Title :

    An Adaptive Nonlinear Filter for Uncertain Measurement Noise


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Yu, Xiang (editor) / Dong, Xiangxiang (author) / Zhang, Lulu (author) / Lv, Runyan (author) / Cai, Yunze (author)


    Publication date :

    2021-10-30


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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