Sponsor
The authors gratefully acknowledge the support of the U.S. Office of Naval Research, ONR Undersea Signal Processing.
Published In
JASA Express Letters
Document Type
Article
Publication Date
6-2014
Subjects
Covariance matrices, Eigenvectors, Sonar arrays, Acoustic arrays, Acoustic signal processing
Abstract
In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.
DOI
10.1121/1.4874224
Persistent Identifier
http://archives.pdx.edu/ds/psu/12074
Citation Details
Quijano, J. E., & Zurk, L. M. (2014). An eigenvector-based test for local stationarity applied to array processing. Journal Of The Acoustical Society Of America, 135(6), EL277-EL283. doi:10.1121/1.4874224
Included in
Categorical Data Analysis Commons, Electromagnetics and Photonics Commons, Signal Processing Commons
Description
Copyright 2014 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The following article appeared in JASA Express Letters and may be found at http://dx.doi.org/10.1121/1.4874224