DocumentCode
942837
Title
Multiple invariance ESPRIT
Author
Swindlehurst, A. Lee ; Ottersten, Björn ; Roy, Richard ; Kailath, Thomas
Author_Institution
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
Volume
40
Issue
4
fYear
1992
fDate
4/1/1992 12:00:00 AM
Firstpage
867
Lastpage
881
Abstract
A subspace-fitting formulation of the ESPRIT problem is presented that provides a framework for extending the algorithm to exploit arrays with multiple invariances. In particular, a multiple invariance (MI) ESPRIT algorithm is developed and the asymptotic distribution of the estimates is obtained. Simulations are conducted to verify the analysis and to compare the performance of MI ESPRIT with that of several other approaches. The excellent quality of the MI ESPRIT estimates is explained by recent results which state that, under certain conditions, subspace-fitting methods of this type are asymptotically efficient
Keywords
signal processing; asymptotic distribution; multiple invariance ESPRIT algorithm; performance; signal parameter estimation; signal processing; simulations; subspace-fitting methods; Analytical models; Frequency estimation; Parameter estimation; Sensor arrays; Signal analysis; Signal processing algorithms; Signal resolution; Space technology; State estimation; Time series analysis;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.127959
Filename
127959
Link To Document