Signal Processing for UnderSea Remote Sensing
Abstract
Many new technologies are being developed for advanced acoustic remote sensing in littoral environments. Many of these technologies (e.g. ATLAS, LCSAS, SSAM II, SSAMIII, etc.) are capable of generating very high-resolution images of underwater phenomena, such as backscattering from objects or sediment. Additionally, some of these sensors give near real-time acoustic feedback about the environment, which in turn aids obstacle avoidance and or route planning for underwater vehicles. In extremely dynamic environments it has been observed that various watercolumn phenomenon can manifest in imagery as strong scatterers. Examples of watercolumn features include clouds of bubbles, impedance discontinuities from changes in salinity, suspended particles, clouds of fish, etc. It would be extremely useful for purposes of environmental characterization, obstacle avoidance and route planning it would be useful to automatically sense and characterize these scatterers. The proposed effort is to aid in the physical and signal processing aspects of upcoming experiments utilizing the ATLAS and LCSAS to acoustically identify and characterize watercolumn scatterers.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 23, 2016
- Source ID
- N000141613145
Entities
People
- Timothy Marston
Organizations
- Office of Naval Research
- United States Navy
- University of Washington