A network of drifting sensors, such as hydrophones mounted to freely drifting buoys, can be used as an array for locating acoustic sources underwater. However, for accurate localization of such… Click to show full abstract
A network of drifting sensors, such as hydrophones mounted to freely drifting buoys, can be used as an array for locating acoustic sources underwater. However, for accurate localization of such a source using coherent processing, the positions of the sensors need to be known to a high degree of accuracy, typically more accurately than provided by dead reckoning or GPS alone. Past work has demonstrated the inter-sensor distances can be obtained from long-term ambient noise correlations on fixed arrays [Sabra et al., IEEE J. Ocean Engineering, 2005, 30]. Here, the approach was extended for tracking drifting sensor motion by combining a stochastic search algorithm with ambient noise correlation processing. Optimization of the stochastic search method was explored and performance compared to acoustic data collected from a volumetric hydrophone vs. vector sensor array deployed in the Long Island Sound.
               
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