Title :
Bayesian sensor fusion for land-mine detection using a dual-sensor hand-held device
Author :
Prado, Jose ; Cabrita, Goncalo ; Marques, Lino
Author_Institution :
Dept. of Electr. Eng. & Comput., Univ. of Coimbra, Coimbra, Portugal
Abstract :
This work presents a methodology and practical implementation of sensor fusion for land-mine detection using a novel multi-sensor hand-held device composed by a triple coil metal detector and a gas sensor. The proposed approach consists on merging data from both sensors in order to reduce the false alarm rate, particularly by using odor information. A Bayesian approach is proposed for the sensor fusion. Results show a false alarm rate of 1.4 to 1, a mine detection rate of 100% and a mine localization mean absolute error of 3 cm. Furthermore the resulting mine presence probability distribution maps represent an important visualization tool for mine clearance hand-held device users.
Keywords :
Bayes methods; coils; electronic noses; geophysical equipment; geophysical techniques; landmine detection; metal detectors; probability; sensor fusion; Bayesian sensor fusion; dual-sensor handheld device; false alarm rate reduction; gas sensor; landmine detection; mine clearance handheld device user; mine localization mean absolute error; mine presence probability distribution map; multisensor handheld device; odor information; triple coil metal detector; Bayes methods; Coils; Detectors; Explosives; Fuel processing industries; Metals; Sensor fusion;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6699756
