Ocean Ambient Noise Studies for Improved Sonar Processing
Abstract
The purpose of this research is to investigate multipath arrival structures that are present in received passive sonar data and exploit this for enhanced passive sonar detection and tracking capability. Inherent in passive sonar systems are several challenges that any effective system implementation must address. One of these challenges is how to best treat multipath arrivals. In some cases these can be a hindrance while in this research they are exploited. In certain environments, multipath arrivals retain significant coherence with respect to each other. This fact has been noted and exploited in recent decades with the development of the class of techniques known as matched field processing (MFP). While there has been a significant amount of academic focus on developing this approach in the context of the more established array processing methodologies, its practical adoption has been hampered due to the need for accurate environmental models. Despite this shortfall, the conceptual basis of using multipath arrivals to enhance target localization still holds promise. In this project, the emphasis is on analytically and experimentally determining techniques to measure and utilize multipath. Recent studies into localization of marine mammals have shown that with only rough environmental models, 3-D localization is possible using a single hydrophone [Tiemann, 2006]. The principle of using multipath for range-depth localization is not new, however until recently the computational complexity of applying this to azimuth-dependent bathymetry has been prohibitive. Whale clicks are impulsive, so multipath structure is evident in raw time-domain data. However, this is not true of vessel noise, so this localization concept is extended to pulse compressed time-series data [See publication #1].
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2013
- Accession Number
- ADA599088
Entities
People
- John Gebbie
- Martin Siderius
Organizations
- Portland State University