Electromagnetic methods for UXO discrimination

NATO Science for Peace and Security Series B: Physics and Biophysics

Volumn , Issue , 2009, Pages 197-221

  O'Neill, Kevin ^a   Fernández, Juan Pablo ^b  

^a Engineering Research and Development Center   (United States)

^b DARTMOUTH COLLEGE   (United States)

Author keywords

Dipole moment; Discrimination; Electromagnetic induction; EMI; Excitation mode; Ground response; Magnetic charge; Magnetic diffusion; Magnetic dipole; Magneto quasistatics; Magnetometry; MQS; Pattern matching; SEA; Standardized excitations approach; UXO

Indexed keywords

EID: 77951443713     PISSN: 18746500     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-4020-9253-4_10     Document Type: Article

References (26)

1. Barrowes, B.E., O'Neill, K., Grzegorczyk, T.M., Chen, X., Kong, J.A.: Broadband analytical magneto-quasistatic electromagnetic induction solution for a conducting and permeable spheroid. IEEE Trans. Geosci. Remote Sensing 42, 2479-2489 (2004)
2. Boser, B.E., Guyon, I.M., Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: D. Haussler (ed.) Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, pp. 144-152. ACM Press, New York (1992)
3. Burges, C.J.C.: A tutorial on Support Vector Machines for pattern recognition. Data Min. Knowl. Disc. 2, 121-167 (1998) (Pubitemid 128695475)
4. Butler, D.K.: Implications of magnetic backgrounds for unexploded ordnance detection. J. Appl. Geophys. 54, 111-125 (2003)
5. Cattach, M.K., Stanley, J.M., Lee, S.J., Boyd, G.W.: Sub-Audio-Magnetics (SAM): a highresolution technique for simultaneously mapping electrical and magnetic properties. Explor. Geophys. 24, 387-400 (1993). See also http://www.g-tek.biz/library.html
6. Chen, C.C., Higgins, M.B., O'Neill, K., Detsch, R.: Ultrawide-bandwidth fully-polarimetric ground penetrating radar classification of subsurface unexploded ordnance. IEEE Trans. Geosci. Remote Sensing 39, 1221-1230 (2001) (Pubitemid 32611023)
7. Chen, X., O'Neill, K., Barrowes, B.E., Grzegorczyk, T.M., Kong, J.A.: Application of a spheroidal mode approach with differential evolution in inversion of magnetoquasistatic data for UXO discrimination. Inv. Prob. 20, 27-40 (2004) (Pubitemid 40002886)
8. Chen, X., O'Neill, K., Grzegorczyk, T.M., Kong, J.A.: Spheroidal mode approach for the characterization of metallic objects using electromagnetic induction. IEEE Trans. Geosci. Remote Sensing 45, 697-706 (2007) (Pubitemid 46375742)
9. Cheng, D.K.: Field and Wave Electromagnetics. Addison-Wesley, Reading, MA (1989)
10. Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, Cambridge (2000)
11. Ferńandez, J.P., Barrowes, B., O'Neill, K., Paulsen, K., Shamatava, I., Shubitidze, F., Sun, K.: Evaluation of SVM classification of metallic objects based on a magnetic-dipole representation. In: J.T. Broach, R.S. Harmon, J.H. Holloway Jr. (eds.) Detection and Remediation Technologies for Mines and Minelike Targets XI, Proceedings of SPIE, vol.6217, pp. 6217-6303 Bellingham, WA (2006) (Pubitemid 44243192)
12. Ferńandez, J.P., Barrowes, B., O'Neill, K., Shamatava, I., Shubitidze, F., Sun, K.: A dataderived time-domain SEA for UXO identification using the MPV sensor. In: R.S. Harmon, J.T. Broach, J.H. Holloway Jr. (eds.) Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII, Proceedings of SPIE, vol.6953, pp. 6953-1H. Bellingham,WA (2008) (Pubitemid 351746652)
13. Ferńandez, J.P., Sun, K., Barrowes, B., O'Neill, K., Shamatava, I., Shubitidze, F., Paulsen, K.: Inferring the location of buried UXO using a Support Vector Machine. In: R.S. Harmon, J.T. Broach, J.H. Holloway Jr. (eds.) Detection and Remediation Technologies for Mines and Minelike Targets XII, Proceedings of SPIE, vol.6553, pp. 6553-0B. Bellingham, WA (2007) (Pubitemid 350069129)
14. O'Neill, K.: Ultra-wideband, fully polarimetric ground penetrating radar for UXO discrimination. ESTCP Final Technical Report, Project 199902. www.estcp.org (2005)
15. O'Neill, K.: Processing for clutter evasion in UXO discrimination. SERDP Project MM-1590 Final Technical Report. www.serdp.org (2008)
16. Pasion, L.R., Oldenburg, D.W.: A discrimination algorithm for UXO using time domain electromagnetics. J. Environ. Eng. Geophys. 6, 91-102 (2001)
17. R̈uping, S.: mySVM-Manual. University of Dortmund, Lehrstuhl Informatik 8 (http://wwwai. cs.uni-dortmund.de/SOFTWARE/MYSVM/) (2000)
18. Shubitidze, F., O'Neill, K., Barrowes, B., Shamatava, I., Sun, K., Ferńandez, J.P., Paulsen, K.: Application of the normalized surface magnetic charge model to UXO discrimination in cases with overlapping signals. J. Appl. Geophys. 61, 292-303 (2007) (Pubitemid 46291671)
19. Shubitidze, F., O'Neill, K., Shamatava, I., Sun, K., Paulsen, K.D.: Fast and accurate calculation of physically complete EMI response by a heterogeneous metallic object. IEEE Trans. Geosci. Remote Sensing 43, 1736-1750 (2005) (Pubitemid 41329023)
20. Stratton, J.A.: Electromagnetic Theory. McGraw-Hill, New York (1941)
21. Sun, K., O'Neill, K., Shubitidze, F., Shamatava, I., Paulsen, K.: Fast data-derived fundamental spheroidal excitation models with application to UXO discrimination. IEEE Trans. Geosci. Remote Sensing 43, 2573-2583 (2005) (Pubitemid 41640781)
22. Vapnik, V.N.: An overview of statistical learning theory. IEEE Trans. Neural Netw. 10, 988-999 (1999)
23. Wait, J.R.: A conducting sphere in a time varying magnetic field. Geophysics 16, 666-672 (1951)
24. Zhang, B.: Classification, identification, and modeling of unexploded ordnance in realistic environments. Ph.D. thesis, Massachusetts Institute of Technology (2008)
25. Zhang, B., O'Neill, K., Kong, J.A., Grzegorczyk, T.M.: Support vector machine and neural network classification of metallic objects using coefficients of the spheroidal MQS response modes. IEEE Trans. Geosci. Remote Sensing 46, 159-171 (2008) (Pubitemid 350281149)
26. Zhang, B., O'Neill, K., Kong, J.A.: Absolute calibration of EMI measurements and application to soil magnetic susceptibility inference. J. Environ. Eng. Geophys. 13, 223-235 (2008)