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3 May 2016 Dynamic EMI sensor platform for digital geophysical mapping and automated clutter rejection for CONUS and OCONUS applications
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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.
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Stephen J. Laudato, Gregory Schultz, Joe Keranen, and Jonathan S. Miller "Dynamic EMI sensor platform for digital geophysical mapping and automated clutter rejection for CONUS and OCONUS applications", Proc. SPIE 9823, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, 982305 (3 May 2016);

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