24 August 1999 Statistical models for the classification of vehicles in MMW imagery
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Abstract
In this paper we exploit high resolution millimeter wave radar ISAR imagery to develop a vehicle classification algorithm, which is robust to orientation and position of the vehicle in the scene. A template based approach is presented and the effect of a number of methods of creating templates investigated. To incorporate the effect of uncertainty in vehicle position and orientation, an approach based on mixture models is developed. The specification of the model is discussed and various approaches for determining the parameters of the model have been assessed. Preliminary results using mixture models to model vehicle signatures and uncertainties in position and orientation are presented. The models and techniques reported here provide a robust approach for general radar classification problems that incorporates uncertainty in a principled manner and improves generalization.
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William Denton, William Denton, Ralph Jackson, Ralph Jackson, Catherine Lawlor, Catherine Lawlor, Adrian Britton, Adrian Britton, Andrew R. Webb, Andrew R. Webb, } "Statistical models for the classification of vehicles in MMW imagery", Proc. SPIE 3718, Automatic Target Recognition IX, (24 August 1999); doi: 10.1117/12.359955; https://doi.org/10.1117/12.359955
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