Advanced UXO Detection and Discrimination Using Magnetic Data Based on Extended Euler Deconvolution and Shape Identification Through Multipole Moments

Abstract : This is the final report for SERDP project MR-1638 and it covers the research results accomplished throughout the project s life. The basic premise of the project is the development of a comprehensive approach for detecting UXO-like targets in the presence of geologic noise, and discrimination between UXO and non-UXO through indirect shape information contained within the magnetic higher-order moments. The first principal task of the project was the continued development and testing of a new method for UXO anomaly detection using a Hilbert transform-based extended Euler deconvolution. The second major task of this project focused on the difficulty of discriminating UXO from non-UXO items with real data when sensor data are strongly contaminated with geological and cultural noise. Successful detection of UXO in these magnetic environments requires detecting all dipole-like magnetic anomalies and identifying and discarding the geologic anomalies that drastically increase the number of false targets. The final major project task takes discrimination between UXO and non-UXO beyond the current dipole-based approaches by utilizing the higher order magnetic moments that encode shape information about buried targets. Throughout this project, we have developed several robust inversion algorithms tailored to the complex nature of the solution space and applied the techniques to both realistic synthetic scrap/UXO models, as well as highest quality data from real targets.

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