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Proceedings Paper

A combined joint diagonalization-MUSIC algorithm for subsurface targets localization
Author(s): Yinlin Wang; John B. Sigman; Benjamin E. Barrowes; Kevin O'Neill; Fridon Shubitidze
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Paper Abstract

This paper presents a combined joint diagonalization (JD) and multiple signal classification (MUSIC) algorithm for estimating subsurface objects locations from electromagnetic induction (EMI) sensor data, without solving ill-posed inverse-scattering problems. JD is a numerical technique that finds the common eigenvectors that diagonalize a set of multistatic response (MSR) matrices measured by a time-domain EMI sensor. Eigenvalues from targets of interest (TOI) can be then distinguished automatically from noise-related eigenvalues. Filtering is also carried out in JD to improve the signal-to-noise ratio (SNR) of the data. The MUSIC algorithm utilizes the orthogonality between the signal and noise subspaces in the MSR matrix, which can be separated with information provided by JD. An array of theoreticallycalculated Green’s functions are then projected onto the noise subspace, and the location of the target is estimated by the minimum of the projection owing to the orthogonality. This combined method is applied to data from the Time-Domain Electromagnetic Multisensor Towed Array Detection System (TEMTADS). Examples of TEMTADS test stand data and field data collected at Spencer Range, Tennessee are analyzed and presented. Results indicate that due to its noniterative mechanism, the method can be executed fast enough to provide real-time estimation of objects’ locations in the field.

Paper Details

Date Published: 9 June 2014
PDF: 10 pages
Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 90720G (9 June 2014); doi: 10.1117/12.2050787
Show Author Affiliations
Yinlin Wang, Dartmouth College (United States)
John B. Sigman, Dartmouth College (United States)
Benjamin E. Barrowes, Dartmouth College (United States)
U.S. Army Engineer Research and Development Ctr. (United States)
Kevin O'Neill, Dartmouth College (United States)
U.S. Army Engineer Research and Development Ctr. (United States)
Fridon Shubitidze, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 9072:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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