Optimal state estimation requires information about noise and initial values, which is not always available. The requirement of initial values is canceled in the optimal unbiased or maximum likelihood estimators, which still require accurate noise information. Designed to satisfy only the unbiasedness constraint, Unbiased finite impulse response (UFIR) estimator discards all other requirements and in many cases justifies suboptimality by being more robust. This chapter discusses different kinds of UFIR state estimators, mainly filters and smoothers and, to a lesser extent, predictors. Various types of smoothers can be designed using the UFIR approach, although many of them appear to be equivalent as opposed to optimal finite impulse response smoothing. UFIR filter can also be generalized for Gauss‐Markov colored noise, if we take into account that unbiased averaging ignores zero mean noise.


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    Title :

    Unbiased FIR State Estimation


    Contributors:


    Publication date :

    2022-08-09


    Size :

    62 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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