On the Sensitivity of Time-Reversal Imaging Techniques to Model Perturbations

Time-reversal (TR) techniques involve physical or synthetic retransmission of signals acquired by a set of transceivers in a time-reversed fashion, and can be used for a host of applications, including ultrawideband imaging of obscured targets. This work investigates the performance of some TR-based techniques under non-ideal conditions, and is divided into three main parts. In the first part, we investigate the robustness of TR-based imaging techniques via the decomposition of TR operator (DORT) algorithm and the multiple signal classification (MUSIC) algorithm under clutter and (additive) noise. In the second part, we examine the effect of TR-invariance breaking (due to losses in the intervening media) on the performance of both DORT and (TR-based) MUSIC. In the third part, effects of translational perturbations of the TR array are examined, as a class of model perturbations. These ensuing effects are then exploited, in a controlled manner, as a means to extract second-order spatial statistics of the probed media.