Robust Autoproduct-based Techniques for Partially-known Ocean Environments
Abstract
The US Navy uses sonar as its primary means of subsurface remote sensing. Many fine techniques exist for reconnaissance, surveillance, and environmental sensing; and for detection, classification, localization, tracking, and identification of sonar contacts. However, current sonar approaches all utilize signal processing schemes matched to the frequencies of the recorded signals. In 2012, an alternative approach, based on nonlinear surrogate fields known as autoproducts, was developed that allows acoustic array signal processing to take place at frequencies chosen by the sonar system operator that may be above or below the bandwidth of the recorded signals. Since 2012, autoproduct-based sonar techniques have been found to provide unexpected and potentially disruptive new capabilities to existing array signal processing schemes like beamforming and matched field processing. However, all prior autoproduct studies have been based on acoustic fields that could be described with one or twospatial coordinates. Thus, the proposed research projectfocuses on autoproduct fields and autoproduct-based sonar schemes in environments where acoustic fields must be described using allthree spatial coordinates. This research effort lies at the boundary between acoustic propagation and signal processing, and includes analytical, simulation, and experimental components. This effort will culminate with performance analysis and comparisons derivedfrom relevant ocean acoustic-propagation recordings. Approved for public release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 09, 2024
- Source ID
- N000142412572
Entities
People
- David J. Dowling
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy