Electromagnetic Induction Landmine Detection Using Bayesian Model Comparison

Abstract

Electromagnetic induction (EMI) landmine detection can be cast as a Bayesian model comparison problem. The models used for low metallic-content mine detection are based on the equivalent electrical circuit representation of the EMI detection system. The EMI detection system is characterized and modeled by the pulse response of its equivalent circuit. The analytically derived transfer function between the transmitter coil and receiver coil demonstrates that the EMI detection system is a third order system in the absence of a mine and that the presence of a mine adds an additional pole that makes the detection system fourth order. The value of the additional pole is determined by the equivalent inductance and resistance of the mine and is unique for each mine type. This change in system order suggests that measured system pulse responses can be used in conjunction with pulse response models to infer the presence or absence of a landmine. The difficulty of this technique is that the amplitude of the term added to the the system pulse response by the landmine is small compared to the pulse response of the system alone. To test the feasibility of Bayesian inference based EMI landmine detection, an EMI detection system experiment was designed and built. In the experiment the EMI detection system was driven by a broadband maximal-length sequence (MLS) in order to obtain sufficient dynamic range in the measured pulse responses. This paper presents the parameterized pulse response models for the detection system with and without a landmine present and gives appropriate priors for the parameters of these models. This paper also presents the ratios of computed posterior probabilities for the mine and no mine models based on data obtained from the experimental EMI landmine detection system. These odds demonstrate the potential for Bayesian EMI landmine detection.

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