3 May 2017 Characterization of buried targets from planar electromagnetic induction sensor data in a moving reference frame
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Abstract
Handheld electromagnetic induction (EMI) sensors used for detection of buried landmines typically employ planar sensor head geometries comprised of a single transmitter and one or more receiver coils. Such configurations have dominant sensitivities oriented in a single direction and are therefore well-suited for metal detection. However, when one tries to characterize the target with a planar EMI sensor, e.g. reconstruct the parameters of an induced dipole model, the problem becomes challenging, since the target needs to be interrogated by all three orthogonal field components in order to obtain unambiguous results. Sweeping the sensor over a target helps with this issue, since the target gets magnetically illuminated from different directions, however a downside is that the sensor head position needs to be known in a ground reference frame, at each scan location. Although various solutions for sensor head position tracking have been reported, they are all more or less obtrusive when used in field conditions. Also, such systems introduce additional uncertainties, often with non-normal distributions, thus complicating inversion procedures. In this paper, we investigate an alternative approach to dipole-based target characterization, where the problem is analyzed in a moving, sensor-based reference frame by dynamically processing sensor data at each scan location using the extended Kalman filter. For a chosen planar coil geometry and scan pattern, we first analyze the basic stability of a filter, with an emphasis on its local observability. We then show how the target's magnetic polarizabilities and target-to-sensor distance can be simultaneously estimated using EMI data only.
Conference Presentation
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D. Ambruš, D. Ambruš, D. Vasić, D. Vasić, V. Bilas, V. Bilas, } "Characterization of buried targets from planar electromagnetic induction sensor data in a moving reference frame", Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, 1018215 (3 May 2017); doi: 10.1117/12.2262438; https://doi.org/10.1117/12.2262438
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