Paper
31 May 2012 Camp Beale live-site handheld-sensor data inversion and classification using advanced EMI models
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Abstract
ESTCP live-site UXO classification results are presented for cued data collected with two advanced EMI instruments, the cart-based 2 × 2 3D TEMTADS array and the Man Portable Vector (MPV) handheld sensor, at the former Camp Beale in California. There were two sets of targets of interest (TOI): the main set consisted of 105-mm, 81-mm, 60-mm, 37-mm and ISO projectiles, and the other (optional) set comprised site-specific fuzes and fuze fragments of varous sizes. The advanced models used for inversion and classification combine: 1) a joint-diagonalization (JD) algorithm that estimates the number of potential targets generating an anomaly directly from the measured data without need for inversion; 2) the ortho-normalized volume magnetic source (ONVMS) model, which locates targets, represents their EMI responses, and extracts their intrinsic feature vectors; and 3) a Gaussian mixture algorithm that uses extracted discrimination features to classify the corresponding buried objects as TOI or clutter. Initially the data are inverted using a combination of ONVMS and the differential evolution direct-search algorithm; this allows the determination of relevant intrinsic parameters, which in turn are classified by a mixture of clustering and library-matching techniques. This paper describes in more detail the main steps of the classification process and demonstrates the results obtained for the 2 × 2 3D TEMTADS and MPV data taken at Camp Beale, as scored independently by the Institute for Defense Analyses. The advanced models are seen to produce superb classification in both cases.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
I. Shamatava, J. P. Fernández, B. E. Barrowes, K. O'Neill, A. Bijamov, and F. Shubitidze "Camp Beale live-site handheld-sensor data inversion and classification using advanced EMI models", Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 835706 (31 May 2012); https://doi.org/10.1117/12.919586
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KEYWORDS
Data modeling

Electromagnetic coupling

Sensors

Detection and tracking algorithms

Magnetism

3D acquisition

Library classification systems

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