Abstract
A sensor-fused system is being developed for detection of buried land mines. The system uses a ground-penetrating radar, an infrared camera, and an electromagnetic induction sensor. In the current implementation each sensor is used independently, and fusion is performed during post-processing. We briefly describe the sensors and a data collection involving buried mine surrogates. Algorithms for preprocessing and feature extraction are reviewed. To deal with non- coincident sampling we have developed a new feature-level fusion algorithm, which does not require detection and subsequent association of putative targets. Results are presented for fusion of simulated data.
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