Physics-based statistical signal processing for improved landmine detection and classification via decay rate estimation
Target discrimination via decay rate (pole) estimation has been proposed as an effective method for landmine and UXO detection. The physical basis for this strategy is that every object in the target library (i.e., landmine and/or UXO target) possesses a unique set of decay rates, or poles. In theory, these poles can be estimated from the measured EMI response and then utilized for target detection and subsequent discrimination and/or identification. Unfortunately, pole estimation is notoriously difficult and this difficulty adversely impacts target discrimination performance. We present simulation results that show that when the sensor/object orientation is not known, the time-domain signatures of two objects with distinct sets of poles may be indistinguishable. Furthermore, this can occur even when the two sets of poles are not necessarily 'close' to each other. Since the basis for this approach to target detection and identification is that targets are uniquely characterized by their estimated poles, discrimination performance is dependent upon pole estimation performance. The Cramer-Rao lower bound (CRLB), which provides a lower bound on the variance of an unbiased estimator, for the pole and amplitude coefficient estimates is utilized to investigate the fundamental limitations on target discrimination via pole estimation. It is shown how both the sampling strategy (i.e., uniform, geometric, logarithmic sampling) and the number of poles being estimated affect pole estimation performance. Detection and identification results are presented for simulated data.
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