Paper
4 May 2009 Man-portable vector EMI instrument data characterization using the NSMS method
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Abstract
The Man Portable Vector (MPV) instrument is a time-domain handheld electromagnetic induction (EMI) instrument with five vector receivers and subcentimeter positioning accuracy. For cued interrogations, the MPV is designed to discriminate unexploded ordnance (UXO) from non-UXO using models ranging from the simple dipole model to physically complete models such as the Normalized Surface Magnetic Source (NSMS) method. The MPV acquires both EMI data and position at a 10Hz sampling rate resulting in 150 data points per second at each of a user selectable number time channels (typically 30-90) starting at 100 microseconds. Several factors might limit the usefulness of this data under real world conditions including an excess of usable data, noise in the position data, and insufficient coverage of anomalies. In this paper, we investigate the impact these factors have on the accuracy of discrimination results based on both static and dynamic MPV data. We investigate the effect of using only a subset of the data along with averaging techniques to reduce the amount of MPV data from a single anomaly. In addition, we inject various levels of noise into the position of the MPV in order to gauge the robustness of the discrimination results. Data is also selectively considered based on number of receivers and vector component(s). Results suggest that remarkably few data points are required for accurate discrimination results and that the vector receivers and low hardware noise of the MPV lead to robust results even with sparse data or noisy positional data.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Benjamin E. Barrowes, Fridon Shubitidze, Juan P. Fernández, Irma Shamatava, and Kevin A. ONeill "Man-portable vector EMI instrument data characterization using the NSMS method", Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73030V (4 May 2009); https://doi.org/10.1117/12.818804
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Cited by 3 scholarly publications.
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KEYWORDS
Data modeling

Electromagnetic coupling

Data acquisition

Magnetism

Receivers

Sensors

Signal to noise ratio

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