NDLI: Detection tests for array processing in unknown correlated noise fields

Content Provider	IEEE Xplore Digital Library
Author	Stoica, P. Cedervall, M.
Copyright Year	1991
Abstract	This paper introduces two eigenvalue-based rules for estimating the number of signals impinging on an array of sensors along with a spatially correlated noise field. The first rule, called S, is derived under the assumption that the noise spatial covariance is block diagonal or banded. The assumption underlying the second detection rule, named T, is that the temporal correlation of the noise has a shorter length than that of the signals. In both cases, a matrix is built from the array output data covariances, the smallest eigenvalue of which is equal to zero under the hypothesis that the source number is overestimated. The sample distribution of the aforementioned smallest eigenvalue is derived and used to formulate the detection rules S and T. Both these rules are computationally quite simple. Additionally, they can be used with a noncalibrated array. The paper includes numerical examples that lend empirical support to the theoretical findings and illustrate the kind of performance that can be achieved by using the S and T detection rules.
Sponsorship	IEEE Signal Processing Society
Starting Page	2351
Ending Page	2362
Page Count	12
File Size	367322
File Format	PDF
ISSN	1053587X
Volume Number	45
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Testing Array signal processing Eigenvalues and eigenfunctions Sensor arrays Parameter estimation Signal processing Covariance matrix Distributed computing Councils Control systems
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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