Adaptive Focusing for Source Localization in EMI Sensing of Metallic Objects: A Preliminary Assessment

Abstract

This paper considers a technique to deal with the problem of detecting and localizing objects in the data processing of electromagnetic induction (EMI) sensing. The technique is formulated using the concept of source power, which in our case is defined as the averaged sum of squared elements of a dipolar polarizabiltiy tensor over a measured time window for a transient electromagnetic (TEM) system. Under the valid dipole approximation to an EMI target, the source is point-like and therefore should occupy a small volume in space. This is the fundamental basis of the energy focusing technique for localizing a source. To achieve a focusing effect on a specified source, a focusing operator is constructed by minimizing the total output power subject to a unity response constraint for that assumed source. A closed-form expression is derived for source power as a function of a source location and can be used blindly without knowledge of the number of objects. The source power is related to data via a data covariance matrix, which in practice is computed with enough data samples. The experiments were conducted with the simulated and real data collected by a standard Geonics EM-63 system. The results, which we regard as a proof-of-concept, show that the focusing technique, under adequate signal-to-noise ratio (SNR), is able to accurately localize sources and is promising in EMI array processing.

Theoretical Developments in Electromagnetic Induction Geophysics with Selected Applications in the Near Surface

“…Knowledge of the set (H, A, and w) everywhere on the measurement plane is sufficient to retrieve the target's location and magnetic polarizability tensor. Song et al (2008a) have developed a method for determining the location of a buried target from data recorded by an array of electromagnetic induction sensors. Their method is similar in principle to the beamforming concept used for source localization in sonar and radar array processing.…”

Estimating source locations of unexploded ordnance using the multiple signal classification algorithm

“…For example, Shubitidze et al (2007) proposes a method of combining total normalized surface magnetic charge model (NSMC) with a pseudospectral finite difference (PSFD) method for localizing a buried object. (Song et al, 2008) adapt a beamforming technique (Van Veen and Buckley, 1988) to localize sources using traditional monostatic measurements (i.e., transmitters and receivers are colocated).…”