UWB radar detection of targets in foliage using alpha-stable clutter models

Author

Kapoor, R. ; Banerjee, A. ; Tsihrintzis, G.A. ; Nandhakumar, N.

Author_Institution

US Army Res. Lab., Adelph, MD, USA

Volume

35

Issue

3

fYear

1999

fDate

7/1/1999 12:00:00 AM

Firstpage

819

Lastpage

834

Abstract

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 (SαS) 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 SαS CFAR performs better than the Weibull and Gaussian CFAR detectors in detecting obscured targets

Keywords

adaptive signal detection; higher order statistics; image segmentation; probability; radar clutter; radar detection; radar imaging; synthetic aperture radar; CFAR detector; SAR imaging; adaptive detection; alpha-stable clutter models; forest canopy; forest clutter; highly impulsive random process; hypothesis test; image segmentation; impulsive interference; obscured targets; radar imagery; region-adaptive symmetric alpha stable; statistical model; targets in foliage; ultrawideband radar detection; Detectors; Image segmentation; Laboratories; Military aircraft; Military computing; Radar clutter; Radar detection; Radar imaging; Ultra wideband radar; Ultra wideband technology;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.784054

Filename

784054