Broadband source localization using matched correlation processing

Abstract

For many years, model-based signal processing algorithms using Matched Field Processing (MFP) techniques have been analyzed with the goal of improving the capability of passive sonar systems for localizing quiet underwater sources. Recently, researchers at DRDC Atlantic have been investigating Matched Correlation Processing (MCP) as a faster alternative to MFP. In this method, the cross-correlations for a source as measured with a pair of hydrophones in a horizontal array are matched with those generated with a correlation model for many candidate ranges and depths along a candidate bearing. These matches are carried out with a number of hydrophone pairs to form many ambiguity surfaces. The maximum on the average of these surfaces is assumed to yield the best estimate of the source position. By carrying out this procedure over a number of candidate bearings, a full 3-D search for the source location is achieved. Since 2002, a number of localization trials have been carried out east of Nova Scotia, Canada. During those trials, an array was deployed on the sea floor and used to collect acoustic signals from various broadband sources. In this paper, we describe the broadband MCP localization technique and show some localization results from those trials.