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Optical Engineering

Expectation-maximization apprach to target model generation from multiple synthetic aperture radar images
Author(s): John A. Richards; Alan S. Willsky; John W. Fisher
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Paper Abstract

A key issue in the development and deployment of model- based automatic target recognition (ATR) systems is the generation of target models to populate the ATR database. Model generation is typically a formidable task, often requiring detailed descriptions of targets in the form of blueprints or CAD models. We propose a method for generating a 3-D target model directly from multiple SAR images of a target obtained at arbitrary viewing angles. This 3-D model is a parameterized description of the target in terms of its component reflector primitives. We pose the model generation problem as a parametric estimation problem based on information extracted from the SAR images. We accomplish this parametric estimation in the context of data association using the expectation-maximization (EM) method. Our model generation technique operates without supervision and adaptively selects the model order. Although we develop our method in the context of a specific data extraction technique and target parameterization scheme, our underlying framework is general enough to accommodate different choices. We present results demonstrating the utility of our method.

Paper Details

Date Published: 1 January 2002
PDF: 17 pages
Opt. Eng. 41(1) doi: 10.1117/1.1417493
Published in: Optical Engineering Volume 41, Issue 1
Show Author Affiliations
John A. Richards, Massachusetts Institute of Technology (United States)
Alan S. Willsky, Massachusetts Institute of Technology (United States)
John W. Fisher, Massachusetts Institute of Technology (United States)


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