Physics-based classification of targets in SAR imagery using subaperture sequences

Lawrence Carin; Gary Ybarra; Priya Bharadwaj; Paul Runkle

doi:10.1109/icassp.1999.757557

Physics-based classification of targets in SAR imagery using subaperture sequences

Lawrence Carin, Gary Ybarra, Priya Bharadwaj, Paul Runkle

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

It is well known that radar scattering from an illuminated object is often highly aspect dependent. We have developed a multi-aspect target classification technique for SAR imagery that incorporates matching-pursuits feature extraction from each of a sequence of subaperture images, in conjunction with a hidden Markov model that explicitly incorporates the target-sensor motion represented by the image sequence. This approach exploits the aspect dependence of the signal features to facilitate maximum-likelihood identification. We consider SAR imagery containing targets concealed by foliage.

Original language	English (US)
Pages (from-to)	3341-3344
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	6
DOIs	https://doi.org/10.1109/icassp.1999.757557
State	Published - Jan 1 1999
Externally published	Yes

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Generated from Scopus record by KAUST IRTS on 2021-02-09

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JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ER -

Physics-based classification of targets in SAR imagery using subaperture sequences

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