Collaborative Sensing of the Ocean-Atmosphere Interface
Abstract
Funds provided to advance collaborative autonomy for emergent UxV systems for collection of high-resolution datasets to resolve the coupling between the ocean and atmosphere at transient features, such as internal wave fronts. The system will provide the means to improve parameterizations in regional/global models and serve as validation datasets for LES and DNS simulations. Additionally, the se observations will be used to develop data-driven reduced order models of the propagation environments (both sound and electromagn etic) specifically for applications onboard a UxV to allow for environmentally aware autonomy that leverages existent propagation co des. Targeted observation will be guided by remote sensing of the sea surface provided by marine X-band radar whereby time-evolving maps of surface clutter will be processed in real-time using machine learning techniques for automated feature detection and classi fication (internal waves, fronts, Langmuir cells). Features from this overwatch system will queue short-term (hours) missions of a gile UxVs that can rapidly map the atmospheric and oceanic boundary layers. Outfitting a persistent USV with a turbulence profiler a nd UAV dock will provide persistent sampling of the atmospheric and oceanic boundary layers in remote regions. Together this body of work will advance tactically relevant research on collaborative, environmentally-aware missions by UxV teams, data-driven reduced o rder modeling for low-bandwidth communication environments, and provide new observational capabilities for sampling the air-sea inte rface at features of interest.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 20, 2021
- Source ID
- N000142112824
Entities
People
- Sophia Merrifield
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego