Inversion of dynamically repositioned multi-axis electromagnetic data for ordnance characterization

Joe Keranen; Fridon Shubitidze; Lance Besaw; Matthew J Casari; Jonathan Miller; Gregory Schultz

doi:10.1117/12.884380

23 May 2011 Inversion of dynamically repositioned multi-axis electromagnetic data for ordnance characterization

Joe Keranen, Fridon Shubitidze, Lance Besaw, Matthew J Casari, Jonathan Miller, Gregory Schultz

Proceedings Volume 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI; 801708 (2011) https://doi.org/10.1117/12.884380
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

The challenges associated with removing UXO and explosive remnants of war have led to a variety of methods for detection and discrimination of buried metallic objects using time-domain electromagnetic induction (EMI). Recent work has shown that parameters recovered from physics-based inversions can discriminate and classify buried ordnance from non-ordnance. We present results of applying advanced processing to data from a dynamically repositioned multiaxis EMI instrument. Data are collected using an adaptive sampling process to find the center of the anomaly and collect minimal data while maintaining model fidelity. An ortho-normalized volume magnetic source (ONVMS) model is used to resolve various targets at different depths. The ONVMS model is a generalized volume dipole model, with the single dipole model being a special limiting case. Using the ONVMS model, an object's response to a sensor's primary magnetic field is modeled mathematically by a set of equivalent magnetic dipoles distributed inside a volume containing the object. We assess the utility and veracity of the dynamic sampling strategy coupled with the ONVMS model on data acquired over a set of calibration and simulant targets. Rapid target characterization codes are aggregated into a software package with particular focus on ease of use for non-expert users.

Citation Download Citation

Joe Keranen, Fridon Shubitidze, Lance Besaw, Matthew J Casari, Jonathan Miller, and Gregory Schultz "Inversion of dynamically repositioned multi-axis electromagnetic data for ordnance characterization", Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 801708 (23 May 2011); https://doi.org/10.1117/12.884380

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