Optimal forward regression for landmine detection by thermal sensing

Luca Del Vecchio; Paolo Fallavollita; Simone De Marco; Salvatore Esposito; Marco Balsi; Stanislaw Jankowski

doi:10.1117/12.873405

14 September 2010 Optimal forward regression for landmine detection by thermal sensing

Luca Del Vecchio, Paolo Fallavollita, Simone De Marco, Salvatore Esposito, Marco Balsi, Stanislaw Jankowski

Proceedings Volume 7745, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010; 77451R (2010) https://doi.org/10.1117/12.873405
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010, 2010, Wilga, Poland

Abstract

In this paper, starting from the GOFR algorithm, a new Forward Regression algorithm for landmine detection and localization using thermal methods is presented. The efficiency of such algorithm is described by showing a valid representation of the typical temperature waveforms taken after heating the ground surface, and detection of temperature anomalies due to the presence of hidden objects. Optimizations to the algorithm are then showed, with the aim of a significant sampling density reduction in space and time.

Citation Download Citation

Luca Del Vecchio, Paolo Fallavollita, Simone De Marco, Salvatore Esposito, Marco Balsi, and Stanislaw Jankowski "Optimal forward regression for landmine detection by thermal sensing", Proc. SPIE 7745, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010, 77451R (14 September 2010); https://doi.org/10.1117/12.873405

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