Predictions of AcousticS with Smart Experimental Networks of GlidERS
Abstract
Ocean acoustic propagation has frequency-dependent sensitivity to a wide range of scales of ocean variability: from meter-scale gradients in the vertical to range-dependent gradients of hundreds of kilometers. However, complete knowledge of the ocean state is neither obtainable nor essential for acoustic nowcasts and forecasts; instead, accurate and timely knowledge of the acoustic channel between source and receiver may be sufficient. We propose to improve the capability of data-assimilative ocean models to predict acoustic propagation in dynamic oceanography environments. This ambitious experimental research program will pair numerical models with adaptive-sampling gliders to minimize ocean state and acoustics uncertainty. We will contrast starkly different ocean data-assimilation approaches the use of coordinated teams of gliders and the most advanced algorithms on land vs. onboard algorithms paired with fresh data from sensors on the vehicle. Simultaneously, we will collect a paired acoustic and oceanographic data set that will be ideally suited to evaluate and compare novel state estimation and machine learning approaches both on land and at sea. This multi-year effort will include two 30-day focused studies using a fleet of gliders to sample the ocean state along a bearing swath from theposition of a known acoustic source to the first convergence zone (order 100 km). During the experiments, glider teams will send their data back for assimilation into the Navy Coastal Ocean Model (NCOM) using a multi-scale 4D-VAR approach and Guidance for Heterogeneous Observation SysTems (GHOST) will control a subset of glider teams waypoints and pathways. To best capture the acoustic variability of the 100 km swath, we will deploy acoustic source moorings. The frequency range will span from 50 Hz 20kHz. The fleet of gliders will be equipped with acoustic receivers and complement moored acoustic array for additional verification of the acoustic state forecasting. Metrics for success of glider fleet optimization and real-time acoustic state estimation will be determined by conducting experiments that withhold subsets of glider resources for comparison of different approaches including standard glider sampling. The experiments will take place during strong changes in stratification and sound speed profile structure in the dynamically energetic Atlantis II Seamount Study area. Results of these studies will be used to address the overall research goals of the project and lay the groundwork for a significant advancement in the fidelity of the acoustic soundscape available to undersea vehicles upon which they rely to complete their missions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2021
- Source ID
- N000142112422
Entities
People
- Travis N Miles
Organizations
- Office of Naval Research
- Rutgers University
- United States Navy