13 August 2002 Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data
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Abstract
Here we consider the use of model-based methods for the detection of buried objects from a sequence of synthetic aperture images obtained by a radar sensor moving linearly down a track. The scattering physics of the underlying sensing modality cause the relevant target signatures to change in a complex yet predictable manner as new images are obtained. To arrive at a tractable processing scheme which exploits these motion-induced changes, we develop a flexible parametric model capable of capturing the full variation of these signatures. A detection method based on a principal components analysis of estimated model vectors is then derived. Results are demonstrated using field data from a forward-looking sensor designed for landmine remediation.
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Jie Cheng, Jie Cheng, Eric L. Miller, Eric L. Miller, } "Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); doi: 10.1117/12.479102; https://doi.org/10.1117/12.479102
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