Paper
5 June 1995 Multiresolution generalized likelihood ratio detection approach to target screening in synthetic aperture radar data
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Abstract
We present a detection concept for initial target screening based on features that are derived from a multiresolution decomposition of synthetic aperture radar (SAR) data. The physical motivation of the multiresolution feature-based approach is the exploitation of signature oscillations produced by the interference between prominant scatterers in cultural objects when resolution is varied. We develop a generalized likelihood ratio test detector which differentiates between first order autoregressive multiresolution processes attributed to different spatial areas. We then derive two special cases of this detector motivated by arguments regarding the clutter statistics. We show that these schemes significantly outperform a standard energy detector operating on the finest available SAR resolution only.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nikola S. Subotic, Leslie M. Collins, Michael F. Reiley, and John D. Gorman "Multiresolution generalized likelihood ratio detection approach to target screening in synthetic aperture radar data", Proc. SPIE 2487, Algorithms for Synthetic Aperture Radar Imagery II, (5 June 1995); https://doi.org/10.1117/12.210840
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Autoregressive models

Synthetic aperture radar

Image resolution

Target detection

Sensors

Process modeling

Radar

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