On some options for statistical classification of buried objects from spatially sampled time or frequency domain EMI data

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On some options for statistical classification of buried objects from spatially sampled time or frequency domain EMI data

Miller, E.

Methods for classifying objects based on spatially sampled electromagnetic induction data taken in the time or frequency domain are developed and analyzed. To deal with nuisance parameters associated with the position of the object relative to the sensor as well as the object orientation a computationally tractable physical model explicit in these unknowns is developed. The model is also parameterized by a collection of decay constants (or equivalently Laplace-plane poles) whose values in theory are independent of object position and orientation. These poles can be used as features for classification. The overall algorithm consists of two stages. First we estimate the values of the unknown parameters and then we do classification. Three classification schemes are examined. The first is based on data residuals. The second uses estimated pole values. The third is a blending of the first two. Preliminary results on synthetic data indicate the robustness of the pole estimates as features for classification and point toward the need for further analytical as well as experimental evaluation of the proposed methods.