Paper
15 September 1998 Method using multiple models to superresolve SAR imagery
Frank M. Candocia, Jose C. Principe
Author Affiliations +
Abstract
This paper introduces a methodology for the superresolution of synthetic aperture radar (SAR) images using multiple target and clutter models. The system has two major components: a mechanism that selects the appropriate model for superresolution and a bank of model estimators to accomplish the superresolution. The typical point scatterer model is incorporated into this technique as well as a model for clutter. Other models can be naturally incorporated. This methodology is flexible in that it can utilize many of the well-known modern spectral estimation techniques. The ability to more accurately model targets using models other than the point scatterer as well as the importance of including models for clutter into a superresolution paradigm is addressed. These issues are shown to be relevant to the automatic target recognition/detection problem. We present a comparison of our technique with other SAR imaging methods and discuss the relative benefits afforded by such an approach.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frank M. Candocia and Jose C. Principe "Method using multiple models to superresolve SAR imagery", Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); https://doi.org/10.1117/12.321824
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Cited by 5 scholarly publications.
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KEYWORDS
Synthetic aperture radar

Fourier transforms

Target detection

Super resolution

Data modeling

Image processing

Statistical modeling

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