DocumentCode
3003132
Title
Performance analysis of the MUSIC algorithm
Author
Spielman, Daniel ; Paulraj, A. ; Kailath, Thomas
Author_Institution
Stanford University, Stanford, CA
Volume
11
fYear
1986
fDate
31503
Firstpage
1909
Lastpage
1912
Abstract
The MUSIC algorithm is one of the more important high resolution approaches for direction finding and spectral estimation that have been developed in recent years. Asymptotically (i.e. infinite data or SNR) the MUSIC algorithm has been shown to yield efficient unbiased estimates. However the performance of the algorithm for the non-asymptotic situation of high noise and limited data has not been fully addressed. In this paper we study the performance of the MUSIC algorithm when only finite noise corrupted data is available. We focus on the role of array design in the performance of MUSIC algorithm for direction finding and introduce certain measures to characterize its performance. We show that in the single target situation these measures can be described in terms of the familiar conventional beampatterns. Results of computer simulations carried out to check the usefulness of such measures are also presented.
Keywords
Contracts; Covariance matrix; Eigenvalues and eigenfunctions; Information systems; Laboratories; Matrix decomposition; Multiple signal classification; Performance analysis; Testing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '86.
Type
conf
DOI
10.1109/ICASSP.1986.1168872
Filename
1168872
Link To Document