Dictionary matching techniques have been an e ective way to detect the location and orientation of buried targets using electromagnetic induction (EMI) sensors. Two problems with dictionary detection are that they require a large amount of computer storage to enumerate nine dimensions, and fine discretization of the parameter space must be used to reduce modeling error. The proposed method shrinks the dictionary size by five orders of magnitude, and reduces modeling error by directly solving for the 3×3 tensor model of the target. A robust lowrank matrix approximation algorithm has been implemented which can also account for directional insensitivities in the measurements.

Date Published: 7 June 2013
PDF: 12 pages
Proc. SPIE 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII, 87090C (7 June 2013); doi: 10.1117/12.2018019

Published in SPIE Proceedings Vol. 8709:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII
J. Thomas Broach; Jason C. Isaacs, Editor(s)