1 January 2002 Expectation-maximization apprach to target model generation from multiple synthetic aperture radar images
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Optical Engineering, 41(1), (2002). doi:10.1117/1.1417493
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.
John A. Richards, Alan S. Willsky, John W. Fisher, "Expectation-maximization apprach to target model generation from multiple synthetic aperture radar images," Optical Engineering 41(1), (1 January 2002). https://doi.org/10.1117/1.1417493
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