Unmanned vehicle navigation concerns estimating attitude, position, and linear velocity of the vehicle the six degrees of freedom (6 DoF). It has been known that the true navigation dynamics are highly nonlinear modeled on the Lie Group of SE2(3). In this paper, a nonlinear filter for inertial navigation is proposed. The filter ensures systematic convergence of the error components starting from almost any initial condition. Also, the errors converge asymptotically to the origin. Experimental results validates the robustness of the proposed filter.


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    Title :

    Nonlinear Deterministic Filter for Inertial Navigation and Bias Estimation with Guaranteed Performance


    Contributors:


    Publication date :

    2021-09-19


    Size :

    1717005 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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