A parameter transformation for improved decay rate estimation

Decay rate estimation has been proposed as an effective method for landmine and unexploded ordnance (UXO) detection and discrimination when electromagnetic induction (EMI) sensors are employed. The phenomenological 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 that are dependent upon the physical characteristics of the target of interest. In theory, these decay rates can be estimated from the measured EMI response and then utilized for target detection and subsequent discrimination and/or classification. Since the basis for this approach to target detection and identification is that targets are uniquely characterized by their decay rates, discrimination performance is dependent upon decay rate estimation performance. Unfortunately, decay rate estimation is notoriously difficult, and this difficulty adversely impacts target discrimination performance. We propose a parameter transformation to improve both the accuracy and the robustness of decay rate estimation when the decay rates are estimated using nonlinear least squares techniques. We present simulation results showing the improvement in the both the RMS error and the bias of the estimates achieved with the parameter transformation.