Landmine Detection and Discrimination using High-Pressure Waterjets

Daryl G. Beetner, Missouri University of Science and Technology
R. Joe Stanley, Missouri University of Science and Technology
Sanjeev Agarwal, Missouri University of Science and Technology
Deepak R. Somasundaram
Kopal Nema
Bhargav Mantha

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1700

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Abstract

Methods of locating and identifying buried landmines using high-pressure waterjets were investigated. Methods were based on the sound produced when the waterjet strikes a buried object. Three classification techniques were studied, based on temporal, spectral, and a combination of temporal and spectral approaches using weighted density distribution functions, a maximum likelihood approach, and hidden Markov models, respectively. Methods were tested with laboratory data from low-metal content simulants and with field data from inert real landmines. Results show that the sound made when the waterjet hit a buried object could be classified with a 90% detection rate and an 18% false alarm rate. In a blind field test using 3 types of harmless objects and 7 types of landmines, buried objects could be accurately classified as harmful or harmless 60%-90% of the time. High-pressure waterjets may serve as a useful companion to conventional detection and classification methods.