Interpretation of through-the-wall radar imagery by probabilistic volume model building

Zachary Rosenbaum; Bijan G. Mobasseri

doi:10.1117/12.777883

16 April 2008 Interpretation of through-the-wall radar imagery by probabilistic volume model building

Proceedings Volume 6943, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII; 69430T (2008) https://doi.org/10.1117/12.777883
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Using radar in a through-the-wall imaging application is an expanding field of research both for civilian and military uses. Thus far, most of the attention has been directed toward building radar imaging systems to detect objects within a room or building. The resulting images are full of ambiguity and difficult to interpret what the image is displaying. Presented here is a novel approach that addresses the interpretation of the images produced by the aforementioned imaging systems. We propose a classification scheme that provides an interpretation of an urban environment imaged in 3D. This approach builds probabilistic object models from feature vectors extracted from a volumetric radar image. A minimum-distance classifier is used to label radar image data and provide a 3D visualization of an urban scene. Results using real radar backscatter data validate the effectiveness of our method.

Citation Download Citation

Zachary Rosenbaum and Bijan G. Mobasseri "Interpretation of through-the-wall radar imagery by probabilistic volume model building", Proc. SPIE 6943, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII, 69430T (16 April 2008); https://doi.org/10.1117/12.777883

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