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.
Long-Range Trajectory Prediction Errors for Least-Squares Smoothing
IEEE Transactions on Aerospace and Electronic Systems ; AES-7 , 2 ; 248-253
1971-03-01
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Article (Journal)
Electronic Resource
English
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