A Simple Magnetic Charge Model for Classification of Multiple Buried Metallic Objects In Cases With Overlapping Signals

Abstract

This paper presents an application of a simple surface magnetic charge model to discriminate between objects of interest such as unexploded ordnance (UXO) and innocuous items, in cases when signals from buried objects are a mixture of responses from two or more items. In the low frequency (ten’s of Hertz up to several hundred’s of kHz) electromagnetic induction (EMI) sensing considered here, both conduction and displacement currents may be neglected within the medium surrounding a metallic object. Therefore, the scattered magnetic field outside the object is represented in terms of scalar potential fields, from which one can obtain all scattered magnetic fields. While these are time dependent by virtue of forcing functions or boundary conditions, they correspond in structure to static fields. Such fields are appropriately, and readily, produced mathematically by equivalent elementary magnetic charges placed on a convenient fictitious closed surface [1, 2, 3]. This forward model is physically complete in the sense that all heterogeneity, near and far field, and internal interaction effects within the object are included. It is very fast; in particular it can be implemented in inversion calculations on a PC. According to the Gauss’s law, eq =ρ ∇⋅B , the net flux of magnetic field through any closed surface equals the total (equivalent) magnetic charge ρeq inside the surface. The frequency spectrum of this total induced equivalent charge is used here as a discriminant. Based on measured data from two scatterers together, an iterative two step procedure is used in conjunction with the differential evolution (DE) algorithm [4, 5]. One step determines of each object’s location and orientation and the other determines the amplitudes of the responding fictitious magnetic charges. Once the objects are isolated, the total magnetic charge for each is calculated as a function of frequency and compared to cataloged/library data. Finally, blind classification analyses are performed for a single object as well as for multiple subsurface scatterers, when two objects appear simultaneously within the field of view of the sensor. Introduction The contamination of land and water by UXO has been a number one military environmental problem for many years. Electromagnetic induction (EMI) sensing technology has been identified as one of most promising technologies for buried UXO detection as well as discrimination. However, the main problem, namely the ability to distinguish between an actual UXO and harmless fragments, remains open. Recent field experiences showed that about 70 % of remediation cost has been spent on excavating innocuous items. In real field surveys, discrimination is cluttered limited. The false alarm rate produced by clutter is extremely high at intensely contaminated sites, and EMI signals may be a mixture of responses from different metallic targets. In cases with overlapping signatures it’s important to isolate one object form another and to analyze them separately. This requires quite onerous processing. Therefore, forward models representing EMI responses from each scatterer must be very fast