Title :
ESPRIT-estimation of signal parameters via rotational invariance techniques
Author :
Roy, Richard ; Kailath, Thomas
Author_Institution :
Inf. Syst. Lab., Stanford Univ., CA, USA
fDate :
7/1/1989 12:00:00 AM
Abstract :
An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. The technique, when applicable, manifests significant performance and computational advantages over previous algorithms such as MEM, Capon´s MLM, and MUSIC
Keywords :
filtering and prediction theory; signal processing; ESPRIT; array; estimation; least-squares; rotational invariance techniques; sensors; signal parameters; signal processing; signal subspaces; translational invariance structure; Computational efficiency; Direction of arrival estimation; Frequency estimation; Maximum likelihood estimation; Multiple signal classification; Parameter estimation; Sensor arrays; Signal processing; Signal processing algorithms; Time series analysis;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on