Overcoming snapshot-deficient measurements with knowledge-aided approaches
Abstract
The use of knowledge-aided covariance is considered for processing underwater acoustic array data in snapshot-deficient scenarios. The knowledge-aided formalism is a technique that combines array data with a known covariance to produce an invertible estimate. For underwater acoustics, simulations of ambient noise provide the a priori covariance allowing degraded signals to be processed adaptively in situations where the sample covariance matrix is rank-deficient. The method is demonstrated for matched field processing using the 21 element array event S5 from the SWellEx-96 experiment. With five snapshots, the knowledge-aided approach significantly reduces localization ambiguity compared to the adaptive white noise gain constraint processor.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 01, 2022
- Source ID
- 10.1121/10.0010455
Entities
People
- D. J. Brooker
- Kay L Gemba
- Laurie T. Fialkowski
Organizations
- Naval Postgraduate School
- Office of Naval Research
- United States Naval Research Laboratory