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Proceedings Paper

Dynamic EMI sensor platform for digital geophysical mapping and automated clutter rejection for CONUS and OCONUS applications
Author(s): Stephen J. Laudato; Gregory Schultz; Joe Keranen; Jonathan S. Miller
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Paper Abstract

The implementation of new advanced electromagnetic induction (EMI) sensor surveys at sites containing unexploded ordnance (UXO) and explosive remnants of war (ERW) is an effective method for accurate mapping and for discriminating clutter from targets of interest. We present development and integration of a next generation advanced EMI sensor onto a cart-based sensing platform to combine the mapping capability of previous digital geophysical survey instruments with the high-resolution discrimination capability of advanced characterization arrays. The EMI sensor employs a multi-axis receiver configuration to produce data sufficient for anomaly discrimination. We discuss platform design and development, data acquisition and post-processing software development, and results from field tests demonstrating the detection and discrimination capability of the cart-based system. Platform development and design focused on navigation and EMI sensor integration onto a custom, low-noise, metal-free platform. Data acquisition is via an Android application with emphasis on ease-of-use and real-time quality control (QC) of collected data. Post-processing methods emphasize QC, inversion-based anomaly location estimation, and automated or supervised polarizability-based discrimination methods to produce a prioritized dig list. Integration of the detection, clutter rejection and QC methods into the post-processing software module reduces the time required between sensor data collection and generation of a prioritized dig list. System concept of operations (CONOPs), data collection, QC, data processing procedures, and performance against various clutter objects and targets of interest will also be discussed.

Paper Details

Date Published: 3 May 2016
PDF: 10 pages
Proc. SPIE 9823, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, 982305 (3 May 2016); doi: 10.1117/12.2225027
Show Author Affiliations
Stephen J. Laudato, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Gregory Schultz, White River Technologies, Inc. (United States)
Joe Keranen, White River Technologies, Inc. (United States)
Jonathan S. Miller, White River Technologies, Inc. (United States)

Published in SPIE Proceedings Vol. 9823:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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