Methods of clutter rejection are discussed which furnish an inherent counterpart of target tracking and detection algorithms. We describe how nonparametric curve estimation methods reduce the original sensor data to a "signal-plus-noise" model which is well suited for various hypotheses testing and dynamical filtering algorithms. We also verify a "white noise" assumption for the model of residuals.
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Sergei Leonov (2001) studied this question.
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