DocumentCode :
3561222
Title :
Nonlinear Inversion for Multiple Objects in Transient Electromagnetic Induction Sensing of Unexploded Ordnance: Technique and Applications
Author :
Lin-Ping Song ; Pasion, L.R. ; Billings, S.D. ; Oldenburg, Douglas W.
Author_Institution :
Dept. of Earth & Ocean Sci., Univ. of British Columbia, Vancouver, BC, Canada
Volume :
49
Issue :
10
fYear :
2011
Firstpage :
4007
Lastpage :
4020
Abstract :
We develop an inversion technique to process overlapping data that arise from closely spaced targets. In contrast to a usual single-object inversion model, a multiobject problem is more challenging because of the increased number of parameters to be found and because of the additional nonlinearity and nonuniqueness. Our solution strategy is to break down the full problem into a sequence of smaller problems so that optimization is conducted in a lower dimensional model space. In the numerical implementation, a set of nonlinear model parameters, e.g., the locations of the underlying sources, is sought while the set of linear model parameters, i.e., their polarization tensors, are updated accordingly in a nested manner. This is an explicit separable nonlinear optimization technique that we cast. We employ a joint diagonalization to find an average principal direction among multiple magnetic polarizability tensors. Since the principal directions are more sensitive to the inaccuracies in the estimated polarization tensor, we suggest a subsequent procedure to optimize the two sets of parameters: orientation and principal polarizations of objects. For initialization, we propose a selected multistart nonlinear algorithm for source localizations that paves an efficient way to find a good initial guess of model parameters and makes the nonlinear inversion effectively automated. We report the new applications of the technique to the test-stand and field data acquired with next-generation sensor systems of the TEMTADS and MetalMapper and study the issue of the spatial resolution of overlapping anomalies through inversions and using the metric defined as the total uncertainty of the polarizabilities.
Keywords :
electromagnetic induction; inductive sensors; nonlinear programming; object detection; tensors; transient response; weapons; MetalMapper; TEMTADS; linear model parameters; multiobject problem; multiple magnetic polarizability tensor; multiple object nonlinear inversion; multistart nonlinear algorithm; next-generation sensor system; nonlinear model parameters; nonlinear optimization technique; single-object inversion model; source localization; spatial resolution; transient electromagnetic induction sensing; unexploded ordnance; Arrays; Electromagnetic interference; Optimization; Receivers; Sensors; Tensile stress; Transmitters; Electromagnetic induction (EMI); multiple objects; nonlinear inversion; transient response; unexploded ordnance (UXO);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
Conference_Location :
5/12/2011 12:00:00 AM
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2011.2132138
Filename :
5766032
Link To Document :
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