We address the problem of detection of targets obscured by a forest canopy using an ultrawideband (UWB) radar. The forest clutter observed in the radar imagery is a highly impulsive random process that is more accurately modeled with the recently proposed class of alpha-stable processes as compared with Gaussian, Weibull, and K-distribution models. With this more accurate model, segmentation is performed on the imagery into forest and clear regions. Further, a region-adaptive symmetric alpha stable (S/spl alpha/S) constant false-alarm rate (CFAR) detector is introduced and its performance is compared with the Weibull and Gaussian CFAR detectors. The results on real data show that the S/spl alpha/S CFAR performs better than the Weibull and Gaussian CFAR detectors in detecting obscured targets.
UWB radar detection of targets in foliage using alpha-stable clutter models
IEEE Transactions on Aerospace and Electronic Systems ; 35 , 3 ; 819-834
01.07.1999
3860223 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
PAPERS - UWB Radar Detection of Targets in Foliage Using Alpha-Stable Clutter Models
Online Contents | 1999
|Radar Detection of Correlated Targets in Clutter
IEEE | 1986
|Detection of Targets in Foliage
Online Contents | 1995
|Book Review - Millimeter-Wave Radar Targets and Clutter
Online Contents | 2004
|