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SSG Seminar Abstract


An Expectation-Maximization Approach
to Target Model Generation
from Multiple SAR Images

John Richards
SSG Doctoral Student


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. Recently, efforts to generate models from a single 1-D radar range profile or a single 2-D synthetic aperture radar (SAR) image have met with some success. However, the models generated from these data sets are of limited use to most ATR systems because they are not three-dimensional. 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. 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.



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