Matched-field processing for broad-band source localization

In the Hudson Canyon experiment, a sound source moved at a constant depth in 73 m of water while transmitting four tonals. The signal was received on a vertical array of hydrophones that spanned the water column. The data set from this experiment has become a standard test case for studying source tracking using matched field processing. As part of that process it was important to first determine a suitable environment model and demonstrate the feasibility of matched-field processing. In this paper, we provide the background on the original data processing that was done to accomplish this. Several interesting results emerged from that study. Frequency averaging was demonstrated to be extremely beneficial when used with the Bartlett processor. However, the popular Minimum Variance processor performed poorly. Finally we discuss a very simple approach to combining the energy coherently that provided significantly improved results.

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