Title :
Nonparametric methods for clutter removal
Author_Institution :
GlaxoSmithKline, Collegeville, PA, USA
fDate :
7/1/2001 12:00:00 AM
Abstract :
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
Keywords :
filtering theory; radar clutter; radar tracking; target tracking; white noise; clutter rejection; clutter removal; detection algorithms; dynamical filtering algorithms; hypotheses testing; nonparametric curve estimation methods; residuals; signal-plus-noise model; target tracking; white noise; Additive noise; Detection algorithms; Filtering algorithms; Kernel; Mathematical model; Noise measurement; Sensor phenomena and characterization; Smoothing methods; Target tracking; Testing;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
