Moving source localization and tracking based on data

Matched field processing (MFP) was introduced sometimes ago to localize the source in range and depth using acoustic data received on a vertical line array using calculated replica fields to match the data assuming the sound speed and bottom profiles are known. Source location results can be ambiguous due to environmental measurements that are often sparse and not real time - this is known as the environmental mismatch problem. A data-based matched-mode source localization method is proposed in this paper for a moving source, using mode wavenumbers and depth functions estimated directly from the data, without requiring any environmental acoustic information and assuming any propagation model. The method is in theory free of the environmental mismatch problem, since the mode replicas are estimated from the same data used to localize the source. The algorithm is introduced and numerical simulations are given to compare with the original MFP results.