Source Localization in a Channel with a Rough Surface Using a Multi-Rank Capon Algorithm

We consider the problem of acoustic source localization in a shallow water channel, in which the prevailing mechanism of sound scattering is developed wind seas. For the given scenario, an adaptive multi-rank Capon algorithm, which is capable of processing in both the conventional and mode space and localizes the source under conditions of incomplete information on a random propagation channel, is constructed. This method of solving the inverse problem uses the worst-case principle and provides greater stability of the estimation procedure to a mismatch caused by the discrepancy between the true coherence matrix of the signal field and its computational model. The results of statistical modeling, which demonstrate the probabilities of correct source localization depending on the input signal-to-noise ratio and the sample size, are presented. The method is validated using the experimental data observed on a stationary path in the Barents Sea. It has been shown that under real conditions, the presented approach is rather efficient and ensures an acceptable source reconstruction quality without using a computationally intense joint search for both the source coordinates and unknown waveguide parameters.