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.
Nonparametric methods for clutter removal
IEEE Transactions on Aerospace and Electronic Systems ; 37 , 3 ; 832-848
2001-07-01
1600888 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
PAPERS - Nonparametric Methods for Clutter Removal
Online Contents | 2001
|CORRESPONDENCE - Nonparametric Rank Detectors under K-Distributed Clutter in Radar Applications
Online Contents | 2005
|Adaptive spatial-temporal filtering methods for clutter removal and target tracking
Tema Archiv | 2008
|Adaptive Spatial-Temporal Filtering Methods for Clutter Removal and Target Tracking
Online Contents | 2008
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