Applying a volume dipole distribution model to next-generation sensor data for multi-object data inversion and discrimination

Abstract

Discrimination between UXO and harmless objects is particularly difficult in highly contaminated sites where two or more objects are simultaneously present in the field of view of the sensor and produce overlapping signals. The first step in overcoming this problem is estimating the number of targets. In this work an orthonormalized volume magnetic source (ONVMS) approach is introduced for estimating the number of targets, along with their locations and orientations. The technique is based on the discrete dipole approximation, which distributes dipoles inside the computational volume. First, a set of orthogonal functions are constructed using fundamental solutions of the Helmholtz equations (i.e., Green's functions). Then, the scattered magnetic field is approximated as a series of these orthogonal functions. The magnitudes of the expansion coefficients are determined directly from the measurement data without solving an ill-posed inverse-scattering problem. The expansion coefficients are then used to determine the amplitudes of the responding volume magnetic dipoles. The algorithm's superior performance and applicability to live UXO sites are illustrated by applying it to the bi-static TEMTADS multi-target data sets collected by NRL personnel at the Aberdeen Proving Ground UXO teststand site.

Isolating and Discriminating Overlapping Signatures in Cluttered Environments

“…The baseplate produces a signal of comparable magnitude to the mortar with the strongest dipole switching in time from thex direction to theẑ direction. These signatures have been obtained using the method presented in the previous section and have been independently validated [48,49]. The inverted positions, listed in the captions of Figure 7, match the true values with a centimeter accuracy and validate our algorithm as well as the associated TEMTADS model in the case of single targets.…”

“…26 9 Three-target inversions from TEMTADS data. The mortar and the baseplate are held fixed at (x, y, z) = (0, 0, 60) [cm] and (x, y, z) = (50,0,49) [cm], respectively, while the nose-cone moves alongx from case to case. True and inverted positions are given in Table 7.…”

A Complex Approach to UXO Discrimination: Combining Advanced EMI Forward Models and Statistical Signal Processing

“…The main objective of this section is to demonstrate the discrimination performance of the ONVMS model [99] in a live UXO site under realistic field conditions; the method is combined with DE optimization (the two-step approach described in Section 3.3) to determine the locations, orientations, and time-dependent total ONVMS of the subsurface targets. The latter depends on the intrinsic properties of the object in question and can be used for discrimination.…”

Demonstration of Advanced EMI Models for Live-Site UXO Discrimination at Former Camp Butner, North Carolina

“…They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance [14] relative to the previous generation of single-axis monostatic sensors [15][16][17]. To take advantage of the rich data sets that these sensors provide, we recently developed and successfully demonstrated a discrimination-oriented data pre-processing scheme based on joint diagonalization (JD) [13]. Let us illustrate the method by describing its TEMTADS implementation.…”

“…The advanced models we have developed for UXO discrimination include the normalized surface magnetic source (NSMS) model [12] and the orthonormalized volume magnetic source (ONVMS) model [13]. The ONVMS model can be considered as a generalized volume dipole model: in it, an object's response to a sensor is modeled mathematically using a set of equivalent point-like analytic solutions of the Maxwell equations (usually dipoles, though charges are also a possibility) distributed over a computational volume located under an EMI sensor and potentially containing anomalies.…”