Computational analysis of detectability metrics from an EMI sensor for target detection and discrimination

Isaac Chappell II; Robert Kraig; Howard Last

doi:10.1117/12.2021678

7 June 2013 Computational analysis of detectability metrics from an EMI sensor for target detection and discrimination

Isaac Chappell II, Robert Kraig, Howard Last

Proceedings Volume 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII; 87090F (2013) https://doi.org/10.1117/12.2021678
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Many technologies are being developed to improve the detection of buried threats (e.g., landmines) and to discriminate these threats from clutter in an operational environment. Current systems have implemented ground-penetrating radar (GPR) and electromagnetic induction (EMI) sensors. The detection performance of these systems is assessed in field testing, where algorithms are used to determine when a buried threat has been encountered [1]. Similar to work done by Rosen and Ayers [2], this paper focuses on developing a method to study EMI sensor performance independent of any aided target recognition (ATR) algorithm used. Rosen and Ayers developed a method and a simple metric for assessing the mine-detection capabilities of down-looking GPR systems before an ATR algorithm is applied. This paper reports the development of two metrics for a wide-band EMI sensor based on the method used by Rosen and Ayers. In this initial effort, the values of the metrics developed are presented over different targets, and observations are made regarding potential use of this metric.

Citation Download Citation

Isaac Chappell II, Robert Kraig, and Howard Last "Computational analysis of detectability metrics from an EMI sensor for target detection and discrimination", Proc. SPIE 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII, 87090F (7 June 2013); https://doi.org/10.1117/12.2021678

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