Automated matching of long range underwater acoustic arrivals to predictions using a minimum variance Approach

Abstract

An automated method was developed to align underwater acoustic measurements taken at various depths and ranges to a reference model of acoustic arrival structure. Data used to demonstrate the method were collected by four autonomous underwater vehicles deployed in the Philippine Sea as part of an ocean acoustic tomography experiment. The arrivals were measured in the upper 1000 m of the ocean at ranges spanning several hundred kilometers from 5 moored acoustic tomography sources. The primary objective is to accomplish automatic source-receiver ranging by aligning measurements of long range acoustic arrivals to a single reference model. Acoustic arrival time structure for pulse compressed signals at long ranges is relatively stable, yet real ocean variability presents challenges in acoustic arrival matching. The presence of internal waves scatters the acoustic arrival structure and can introduce spurious arrivals in the measured data. This method takes advantage of simple projections of the measured structure onto the model space with constraints informed by scattering statistics consistent with the Garrett Munk internal wave energy spectrum. Compared to manual matching of the measured arrivals to eigenray models, more than 90% of the automatically obtained range estimates were within 150 m of the manually obtained range estimates.