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Detection of buried mines from array inductive measurements

The problem of mine detection and localization from array- based electromagnetic induction data is addressed. An efficient forward scattering model based on the Born approximation is employed. Using insight obtained from this model, a clutter model in the form of a state space system is developed which describes the correlation of the noise both across the sensing array and from one position of the array to the next as the measurement device proceeds down track. A multiple-model detection scheme based on the whitening properties of the Kalman filter is employed to perform the actual mine detection. This approach allows for the detection and localization of buried objects well before the array physically moves over mines. Examples are provided for mines buried directly in front and off to one side of the array.