Detecting buried mines in ground-penetrating radar using a Hough transform approach | Zendy

Mark J. Carlotto | Zendy

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<title>Detecting buried mines in ground-penetrating radar using a Hough transform approach</title>

Author(s) -

Mark J. Carlotto

Publication year - 2002

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.478719

Subject(s) - ground penetrating radar , hough transform , radar , constant false alarm rate , point (geometry) , object (grammar) , geology , computer science , object detection , artificial intelligence , false alarm , computer vision , remote sensing , radar imaging , detector , pattern recognition (psychology) , mathematics , geometry , image (mathematics) , telecommunications

A method for detecting buried mines in ground penetrating radar (GPR) data using a Hough transform approach is described. GPR is one of three sensors used in the Mine Hunter/Killer (MH/K) system for detecting buried mines. A buried mine modeled as a point scatterer in object space gives rise to a hyperbolic response in GPR measurement space. Our approach uses the Hough transform to recover the object space representation (i.e., the location of mines in x, y, and depth) from the GPR data, in effect 'deconvolving' the response of the radar. This is done by having each point in measurement space vote for all points in object space where the mine could be located. Against a baseline energy detector, the Hough algorithm shows a one half order reduction in false alarm rate at a fixed probability of detection for low metal, metal, and non metal mines.

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