Paper
13 August 1999 Statistical modeling of complex target radar cross-section with the beta probability density function
Stephen A. Stanhope, Eric R. Keydel, Wayne D. Williams, Russell Sieron, Vasik G. Rajlich
Author Affiliations +
Abstract
We analyze the use of the beta distribution for the statistical characterization of the radar cross-section (RCS) of a complex target. Analysis consists of first generalizing a complex target as a set of component scatterers, each with a constant component RCS and a phase characterized by a uniform random variable. From this set of target-based component scatterers, estimates of the moments of the implied probability distribution function (pdf) on the RCS response of the full target are gathered, and used to fit a beta distribution. Two distinct methods of fitting the beta distribution are compared against the results of Monte-Carlo analysis over a variety of component scatterer sets. This comparison leads to estimates of the accuracy of each method of generating moments for the fitting of the beta distribution, and further, leads to the characterization of pathological cases for the use of the beta distribution in modeling complex target RCS. Resulting methods for the modeling of the RCS of a complex target are discussed in the context of model-based SAR ATR applications.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen A. Stanhope, Eric R. Keydel, Wayne D. Williams, Russell Sieron, and Vasik G. Rajlich "Statistical modeling of complex target radar cross-section with the beta probability density function", Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); https://doi.org/10.1117/12.357678
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Cited by 2 scholarly publications.
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KEYWORDS
Statistical analysis

Automatic target recognition

Model-based design

Target recognition

Synthetic aperture radar

Scattering

Mathematical modeling

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