A theoretical performance analysis and simulation of time-domain EMI sensor data for land mine detection

In this paper, the physical phenomenology of electromagnetic induction (EMI) sensors is reviewed for application to land mine detection and remediation. The response from time-domain EMI sensors is modeled as an exponential damping as a function of time, characterized by the initial magnitude and decay rate. Currently deployed EMI sensors that are used for the land mine detection process the recorded signal in a variety of ways in order to provide an audio output for the operator to judge whether or not the signal is from a mine. Sensors may sample the decay curve, sum it, or calculate its energy. Based on exponential decay model and the assumption that the sensor response is subject to additive white Gaussian noise, the performance of these, as well as optimal, detectors are derived and compared. Theoretical performance predictions derived using simplifying assumptions are shown to agree closely with simulated performance. It will also be shown that the generalized likelihood ratio test (GLRT) is equivalent to the likelihood ratio test (LRT) for multichannel time-domain EMI sensor data under the additive white Gaussian noise assumption and specific assumptions regarding the statistics of the decay rates of targets and clutter.