Magnetics and electromagnetic surveys are the primary techniques used for UXO remediation projects. Magnetometry is a valuable geophysical tool for UXO detection due to ease of data acquisition and its ability to detect relatively deep targets. However, magnetics data can have large false alarm rates due to geological noise, and there is an inherent non-uniqueness when trying to determine the orientation, size and shape of a target. Electromagnetic surveys, on the other hand, are relatively immune to geologic noise and are more diagnostic for target shape and size but have a reduced depth of investigation. In this paper we aim to improve discrimination ability by developing an interpretation method that takes advantage of the strengths of both techniques. We consider two different approaches to the problem: (1) Interpreting the data sets cooperatively, and (2) Interpreting the data sets jointly. For cooperative inversion information from the inversion of one data set is used as a constraint for inverting another data set. In joint inversion, target model parameters common to the forward solution of both types of data are identified and the model parameters from all the survey data are recovered simultaneously. We compare the confidence with which we can discriminate UXO from non-UXO targets when applying these different approaches to results from individual inversions. In this paper we focus on the details of the joint and cooperative inversion methodologies. Examples of the application of the methodology to TEM and magnetics data sets collected at the former Fort Ord in California are presented. This work is funded in part by the U.S. Army Engineer Research and Development Center and the Army Research Office.
[1]
D. Oldenburg,et al.
DISCRIMINATION AND CLASSIFICATION OF UXO USING MAGNETOMETRY: INVERSION AND ERROR ANALYSIS USING ROBUST STATISTICS
,
2003
.
[2]
John E McFee.
Electromagnetic Remote Sensing. Low Frequency Electromagnetics
,
1989
.
[3]
Cary B. Cox,et al.
Multisensor Methods for Buried Unexploded Ordnance Detection, Discrimination, and Identification
,
1998
.
[4]
W. M. Wynn,et al.
Enhanced clutter rejection with two-parameter magnetic classification for UXO
,
1999,
Defense, Security, and Sensing.
[5]
Leonard R. Pasion,et al.
Discrimination and identification of UXO by geophysical inversion of total-field magnetic data
,
2002
.
[6]
D. Oldenburg,et al.
A Discrimination Algorithm for UXO Using Time Domain Electromagnetics
,
2001
.
[7]
Leonard R. Pasion,et al.
Locating and Characterizing Unexploded Ordnance Using Time Domain Electromagnetic Induction
,
2001
.
[8]
Leslie M. Collins,et al.
A comparison of the performance of statistical and fuzzy algorithms for unexploded ordnance detection
,
2001,
IEEE Trans. Fuzzy Syst..