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- W2014005932 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." @default.
- W2014005932 created "2016-06-24" @default.
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- W2014005932 date "2002-08-12" @default.
- W2014005932 modified "2023-09-23" @default.
- W2014005932 title "<title>Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data</title>" @default.
- W2014005932 doi "https://doi.org/10.1117/12.479102" @default.
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