1 January 2002 Expectation-maximization apprach to target model generation from multiple synthetic aperture radar images
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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.
© (2002) Society of Photo-Optical Instrumentation Engineers (SPIE)
John A. Richards, John A. Richards, Alan S. Willsky, Alan S. Willsky, John W. Fisher, 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 . Submission:

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