This paper presents exact formulas and graphs to determine the root-mean-square error of prediction for position and velocity estimates of an object, based on least-squares smoothing. The prediction interval is taken from an endpoint estimate up to ten times the smoothing interval. The rms values may be used to determine how large a search volume must be to accommodate a substantial data dropout interval.


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    Title :

    Long-Range Trajectory Prediction Errors for Least-Squares Smoothing


    Contributors:


    Publication date :

    1971-03-01


    Size :

    1234802 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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