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Proceedings Paper

APG UXO discrimination studies using advanced EMI models and TEMTADS data
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Paper Abstract

Recently, new generation, relatively sophisticated, ultra wideband EMI sensors with novel waveforms and multi-axis or vector receivers, have been developed which operate either in the time domain or in the frequency domain. Among these emerging technologies is the Time-domain Electromagnetic Multi-sensor Tower Array Detection System (TEMTADS). The system consists of 25 transmit/receive pairs arranged in a 5 × 5 grid, each with a square 35-cm diameter transmitter coil and a concentric square 25-cm receiver coil. The sensor activates the transmitter loops in sequence, and for each transmitter all receivers receive, measuring the complete transient response over a wide dynamic time range going approximately from 100 μs to 25 ms and distributed in 123 time gates. Thus it provides 625 data points at each location, without the need for a relative positioning system due to its fixed geometry. The combination of spatial diversity in the measurements and well-located sensor positions offers unprecedented data quality for discrimination processing algorithms. To take advantage of the data diversity that this instrument provides, we will use both of the following in an analysis of data acquired with the TEMTADS at Aberdeen Proving Ground (APG) in 2008: (1) advanced, physically complete EMI forward models such as the normalized surface magnetic source (NSMS) model and (2) a data-inversion scheme that uses the newly developed HAP method to estimate the location of a target. Initially the applicability of the NSMS and HAP algorithms to TEMTADS data sets are demonstrated by comparing the modeled data to test-stand and calibration data, and then the APG blind discrimination studies are conducted using as discrimination parameters the total NSMS and principal axes of the induced magnetic polarizability tensor for each target. The classification is done on the extracted feature vector via statistical classification tools.

Paper Details

Date Published: 5 May 2009
PDF: 9 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030M (5 May 2009); doi: 10.1117/12.819035
Show Author Affiliations
Fridon Shubitidze, Dartmouth College (United States)
Sky Research, Inc. (United States)
Ben Barrowes, Dartmouth College (United States)
U.S. Army Engineer Research and Development Ctr. (United States)
Irma Shamatava, Dartmouth College (United States)
Sky Research, Inc. (United States)
Juan Pablo Fernández, Dartmouth College (United States)
Kevin O'Neill, Dartmouth College (United States)
U.S. Army Engineer Research and Development Ctr. (United States)


Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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