Time-reversal imaging and classification for distant targets in a shallow water channel

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is capable of performing target classification (in addition to localization). In this paper we apply the time-reversal technique to locate man-made cylindrical targets moving in a shallow ocean channel at long range, as well as to classify them from natural false targets like a school of fish. We present imaging and classification on simulated scattering data, for both target classes. In addition to the imaging, we explore extraction of features from the time-reversal data, with these applied to subsequent target classification. Time-reversal implementation requires a fast forward model, with that implemented here by a normal-mode model. In this paper, we present the underlying theory of TRI, feature extraction and target classification via a relevance vector machine (RVM).