PLATFORM CENTRIC ASW PROCESSING WITH THROUGH-THE-SENSOR DATA ASSIMILATION AND FUSION
Abstract
The proposed work involves harnessing adaptive signal processing with geometric feature extraction and sophisticated ~big data~ mac"hine learning techniques to track, interpret, and learn potentially intertwined signatures of diverse oceanic events in shallow water acoustics. Oceanic phenomenaof interest include but are not limited to multipath acoustic scattering, Doppler effect from fluid motion and moving reflectors in the ocean, high-energy transient events such as surface wave focusing, constructive multipath interference, structured ambient noise, etc. To achieve this end, The simultaneous combination of acoustic and oceanographic data observations, as opposed tothe present sequential approach of predicting the ocean first then using that ocean for acoustic predictions, will be used to demonstrate significant performance enhancement of Anti- Submarine Warfare (ASW) processing. Experimental observations will be made of midfrequency, signal and noise acoustic data coincident with time-evolving, spatially-distributed measurements of the local physical oceanography and synoptic ocean surface wave field. Thetight integration of acoustics and physical oceanography will be implemented through an expanded data assimilation approach yielding a dynamic regional model enforcing consistency between ob"servations of the ocean volume, sea surface, and acoustic propagation.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 20, 2019
- Source ID
- N000141912635
Entities
People
- W. A. Kuperman
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego