Method is presented for relaxing usual assumption in sequential Bayesian or minimum variance estimation that distributions of observation errors are known; approach used is to regard distributions as normal but with unknown variances; applying Bayesian estimation theory in multistage process yields recursive equations for estimating simultaneously system state and variances; equations are like those of Kalman filter but with additional equations adjoined to produce running estimates of unknown variances; application of method to simulated trajectory estimation for interplanetary vehicle and results obtained.


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    Title :

    Sequential estimation of observation error variances in trajectory estimation problem


    Additional title:

    AIAA J


    Contributors:
    Smith, G.L. (author)

    Published in:

    AIAA Journal ; 5 , n 11


    Publication date :

    1967


    Size :

    7 pages


    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English


    Keywords :