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

Abstract

To extract intrinsic polarization parameters of a buried object from electromagnetic induction (EMI) responses, one has to first find its location. We developed an efficient method to find the approximate locations of multiple ordnance items using time domain electromagnetic data. The procedure was based upon the principle of multiple signal classification which exploits the orthogonality of signal and noise subspaces of multistatic EMI data. For an arbitrary multistatic array, we formulated transmitter-based and receiver-based imaging or steering vectorial operators that related with the left and right singular vectors of a multistatic response matrix. The operators were computed at potential source locations and are mapped onto the noise subspaces derived from data. A spatial metric function was therefore introduced to measure the magnitude of the projection. A 3D source imaging of the metric function could be obtained by evaluating all potential locations over a region of interest. In ideal cases, the perfect orthogonality between the computed signal subspace and measured noisy subspace can be achieved at or near a target location, and rendered an imaging peak at that location. Conversely, the peak image locations obtained from this technique were used as the indicators for where targets were most likely present. The number of targets could be estimated from the rank of the data matrix, provided there were a sufficient number of transmitters and receivers. In some instances the locations of multiple targets were imaged directly, but the procedure was enhanced by stripping the effect of a larger or shallower target from the image. The technique was evaluated using the test-stand and field data, and compared with the standard nonlinear inversion. The results showed that it has potential capability to accurately localize sources in EMI sensing.