Abstract

Abstract : The extent of buried munitions and explosives of concern (MEC), or unexploded ordnance (UXO), creates a serious environmental hazard in the U.S., especially where military bases and ranges are being converted to civilian use (millions of acres). The cleanup of these sites presents a formidable challenge to DoD, most prominently in terms of accurate and reliable detection and classification. Discrimination between MEC and relatively safe background clutter (scrap metal) is a monumental problem that depends on the instrument technology, as well as on the processing methodology that inverts the detection data to infer MEC. Reducing the number of false alarms in the detection process can save billions of dollars in the cleanup effort. That process and the consequent savings rely in large part on precise three-dimensional positioning (geolocation) of the detection sensors both to aid in the inversion of the data in post-survey data processing and in the mapping and recovery of locations with positive identification. Although the detection instrument technology has advanced significantly in the last decade, it is often still the geolocation technology that defines or limits the accuracy of MEC detection. The objective of this project was to develop and test novel geolocation algorithms applied to scenarios typical of MEC detection and recovery, where the precision goals are 1 cm and 10 cm for three-dimensional positioning of magnetic and electro-magnetic detection devices. The principal geolocation system was assumed to be based on inertial measurement units (IMUs) integrated with differential GPS. The GPS receiver presumably is of geodetic quality commensurate with the precision goals and serves as the reference system.

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