A Unified Approach to UXO Discrimination Using the Method of Auxiliary Sources

Abstract : The research described in this report was conducted in support of Strategic Environmental Research and Development Program (SERDP) SEED Broad Agency Announcement (BAA), Statement of Need UXSEED-05-02, Innovative Approaches to Unexploded Ordnance (UXO) Cleanup. A SERDP SEED research and development project UX-1446 entitled A Unified Approach to UXO Discrimination Using the Method of Auxiliary Sources was proposed in response to the above BAA. The main emphasis of this research was to explore the fundamental characteristics of the Surface Magnetic Charge (SMC) and Standard Excitation Approach (SEA) methods when applied to UXO discrimination problems. Both methods were derived from the Method of Auxiliary Sources (MAS), and thus represent the secondary magnetic fields from a compact metallic target with a surface of magnetic charge. The SEA and SMC are relatively new modeling techniques for UXO discrimination. Therefore, we investigated some fundamental, as well as practical, characteristics of the forward model. These include the accuracy with which the methods can model sensor data, the speed to carry out the forward modeling, and the type of discrimination algorithms amenable to each of the forward modeling methods. For the SEA, we wanted to determine the ease with which the sources can be derived for a particular target. For the SMC, we wanted to determine if the surface magnetic charge distribution is a good discriminant, and, if so, what algorithm is required to obtain a stable estimate of the magnetic charge.

[1]  D. Oldenburg,et al.  A Discrimination Algorithm for UXO Using Time Domain Electromagnetics , 2001 .

[2]  Walter L. Anderson,et al.  Algorithm 588: Fast Hankel Transforms Using Related and Lagged Convolutions , 1982, TOMS.

[3]  H. Johnson,et al.  A comparison of 'traditional' and multimedia information systems development practices , 2003, Inf. Softw. Technol..

[4]  C. E. Baum.  Simulation of electromagnetic aspects of lightning , 1991 .

[5]  Irma Shamatava,et al.  A hybrid full MAS and Combined MAS/TSA Algorithm for Electromagnetic Induction Sensing , 2004 .

[6]  Kevin O'Neill,et al.  Use of standardized source sets for enhanced EMI classification of buried heterogeneous objects , 2004, SPIE Defense + Commercial Sensing.

[7]  Irma Shamatava,et al.  Fast data-derived fundamental spheroidal excitation models with application to UXO identification , 2004, SPIE Defense + Commercial Sensing.

[8]  Lotfollah Shafai,et al.  Near-zone fields scattered by three-dimensional highly conducting permeable objects in the field of an arbitrary loop , 1991, IEEE Trans. Geosci. Remote. Sens..

[9]  Jin Au Kong,et al.  Broadband analytical magnetoquasistatic electromagnetic induction solution for a conducting and permeable spheroid , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[10]  W. Menke.  Geophysical data analysis : discrete inverse theory , 1984 .

[11]  Irma Shamatava,et al.  Analysis of EMI scattering to support UXO discrimination: heterogeneous and multiple objects , 2003, SPIE Defense + Commercial Sensing.

[12]  G. Arfken.  Mathematical Methods for Physicists , 1967 .

[13]  Carl E. Baum,et al.  On the low-frequency natural response of conducting and permeable targets , 1999, IEEE Trans. Geosci. Remote. Sens..