Title :
Analysis of algorithms for sensor arrays with invariance structure
Author :
Ottersten, Björn ; Viberg, Mats ; Kailath, Thomas
Author_Institution :
Inf. Syst. Lab., Standord Univ., CA, USA
Abstract :
The problem of estimating signal parameters from sensor array data is addressed. If the array is composed of two identical subarrays, (i.e. one invariance) the ESPRIT algorithm is known to yield parameter estimates in a very cost efficient manner. Recently, the total least squares (TLS) version of ESPRIT has been formulated in a subspace fitting framework. In this formulation, the ESPRIT concept is easily generalized to arrays exhibiting more than one invariance. The asymptotic properties for this class of algorithms are derived. The estimates are shown to be statistically efficient under certain assumptions. The case of a uniform linear array is studied in more detail, and a generalization of the ESPRIT algorithm is proposed by introducing row weighting of the subspace estimate
Keywords :
parameter estimation; signal processing; ESPRIT algorithm; TLS version; asymptotic properties; invariance structure; rotational invariance techniques; row weighting; sensor arrays; signal parameters estimation; subspace estimate; total least squares; uniform linear array; Algorithm design and analysis; Calibration; Contracts; Costs; Fitting; Geophysics computing; Laboratories; Least squares methods; Parameter estimation; Sensor arrays; Signal to noise ratio; Tellurium; Yield estimation;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.116247