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Ab s t rac tWe consider the problem of estimating the arrival times of overlapping ocean-acoustic signals from a noisy received waveform which consists of scaled and delayed replicas of a deterministic transient signal. We assume that the transmitted signal and the number of paths in the multipath environment are known, and consider algorithms that give least-squarrs estimates of the amplitude and time delay of each path. The Gauss-Newton algorithm converges quickly to a minimum of the error surface, but if the initial estimates are not sufficiently accurate, only a local minimum will be found. In this paper, we compaw several different methods for obtaining initial estimates including coordinate descent and linear prediction. We demonstrate the performance of the complete algorithm (initial estimates followed by a Gauss-Newton search) on experimental data.

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In practice, if signals are band pass, their baseWe address the problem of multipath time-delay estimation. When the received data is very long compared to the transmitted signal, the data is expected to consist of a large number of paths. Modeling the entire data becomes computationally expensive. We propose a technique to break the data into short segments and model each segment individually without misfitting or truncating any paths at the ends of any segment. By effectively using overlapping segments, the estimates of time-delays are combined to model the entire data record. The method is extended to the case where only basebanded data are available. The proposed technique is demonstrated on an experimental sea-test data.