Leading up to the Apollo missions the Extended Kalman Filter, a modified version of the Kalman Filter, was developed to estimate the state of a nonlinear system. Throughout the Apollo missions, Potter's Square Root Filter was used for lunar navigation. Now that NASA is returning to the Moon, the filters used during the Apollo missions must be compared to the filters that have been developed since that time, the Bierman-Thornton Filter (UD) and the Unscented Kalman Filter (UKF). The UD Filter involves factoring the covariance matrix into UDUT and has similar accuracy to the Square Root Filter; however it requires less computation time. Conversely, the UKF, which uses sigma points, is much more computationally intensive than any of the filters; however it produces the most accurate results. The Extended Kalman Filter, Potter's Square Root Filter, the Bierman-Thornton UD Filter, and the Unscented Kalman Filter each prove to be the most accurate filter depending on the specific conditions of the navigation system.


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    Title :

    Comparison of Nonlinear Filtering Techniques for Lunar Surface Roving Navigation


    Contributors:
    L. Kimber (author) / B. W. Welch (author)

    Publication date :

    2008


    Size :

    20 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English





    Lunar surface navigation for roving vehicle (MOLAB)

    Streicher, M. | Engineering Index Backfile | 1965


    Lunar Roving Vehicle Navigation System Performance Review

    E. C. Smith / W. C. Mastin | NTIS | 1973



    Lunar Roving Vehicle Navigation System Performance Review

    Smith, Earnest C. / Mastin, William C. | NTRS | 1973