Title :
A Kalman filter-based approach to detect landmines from metal detector data
Author :
Abeynayake, Canicious ; Chant, Ian
Author_Institution :
Defence Sci. & Technol. Organ., Salisbury, SA, Australia
Abstract :
Metal detectors play a significant role in landmine detection. Automatic sensor fusion is required to improve the performance of ground penetrating radar (GPR)-metal detector multi-sensor systems. The existing version of the Kalman filter-based detection algorithm has been adapted for automatic detection and discrimination of landmines in metal detector data. In this algorithm, multi-channel metal detector output data are fused to produce a distribution of probabilities of the presence or absence of a target. Performance of this algorithm has been assessed using data obtained by burying a number of simulant landmines, canonical targets and shrapnel in different soil types
Keywords :
Kalman filters; buried object detection; electromagnetic induction; military radar; radar detection; sensor fusion; weapons; Kalman filter-based approach; automatic sensor fusion; canonical targets; discrimination; ground penetrating radar; landmine detection; metal detector data; multi-sensor systems; shrapnel; simulant landmines; soil types; Detectors; Kalman filters; Landmine detection;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.978067
