Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

Gregory M. Schultz; Joe Keranen; Jonathan S. Miller; Fridon Shubitidze

doi:10.1117/12.2050876

9 June 2014 Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

Gregory M. Schultz, Joe Keranen, Jonathan S. Miller, Fridon Shubitidze

Proceedings Volume 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX; 90720H (2014) https://doi.org/10.1117/12.2050876
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

Citation Download Citation

Gregory M. Schultz, Joe Keranen, Jonathan S. Miller, and Fridon Shubitidze "Acquisition and processing of advanced sensor data for ERW and UXO detection and classification", Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 90720H (9 June 2014); https://doi.org/10.1117/12.2050876

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