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Investigating time domain EMI signals diffusion in a conducting environment for UXO detection and classification
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Paper Abstract

This paper investigates diffusion behavior of electromagnetic induction (EMI) signals in multilayer structures to enhance unexploded ordnances (UXO) detection and classification in a marine environment. To date, advanced EMI systems and models have demonstrated excellent classification performance for detecting and discriminating subsurface metallic targets on land. However, the marine environment introduces complexities in both primary and secondary EMI signals. These complexities, such as salinity, air-water-sediment boundaries, etc., could negatively affect target classification performance. The main objective of this paper is to analyze time domain EMI signal diffusion and understand the factors affecting the performance of advanced EMI systems in the marine environment. We use the method of auxiliary sources and the cylindrical plane wave expansion technique to model the performance of current state of the art EMI systems for detecting and classifying underwater UXO in the frequency domain. This model accounts for the spatial (air-sea, and sea-sediment boundaries) and temporal variability of EMI fields in UW environment. Then the corresponding time domain signals are obtained using the Fourier cosine/sine transforms and Anderson filters. While others have shown the significance of environmental EMI response in marine environments, here we focus exclusively on the effect of layer boundaries in that domain. Sensitivity is shown with respect to transmitter coil sizes, sediment conductivity and magnetic permeability, and the target placement in the conducting sediment.

Paper Details

Date Published: 10 May 2019
PDF: 9 pages
Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 110120X (10 May 2019); doi: 10.1117/12.2519213
Show Author Affiliations
Fridon Shubitidze, Dartmouth College (United States)
White River Technologies, Inc. (United States)
Benjamin E. Barrowes, U.S. Army Engineer Research and Development Ctr. (United States)
O'Neill, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 11012:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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