Title :
Estimation of sensor gain and phase
Author :
Fuhrmann, Daniel R.
Author_Institution :
Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA
fDate :
1/1/1994 12:00:00 AM
Abstract :
The problem of estimating the direction-independent gain and phase characteristics of an array of sensors, using knowledge of the true field covariance at the sensor locations, is considered. A concise expression for the log-likelihood function is derived and several mathematical properties of this objective function are given. The Cramer-Rao (C-R) lower bounds on the variances of gain and phase estimates are derived, with the plane wave in isotropic noise considered as a special case. The maximum-likelihood estimates are shown to be consistent, asymptotically efficient and asymptotically normal. A simple estimator is proposed which is consistent and which gives good initial estimates for a Newton algorithm for finding the maximum-likelihood solution. Comparison of the maximum-likelihood estimates and the C-R bounds is given for the plane-wave-in-isotropic-noise example
Keywords :
array signal processing; maximum likelihood estimation; parameter estimation; sensor fusion; Cramer-Rao lower bounds; Newton algorithm; direction-independent characteristics; isotropic noise; log-likelihood function; maximum-likelihood estimates; plane-wave-in-isotropic-noise example; sensor array; sensor gain; sensor phase; true field covariance; Calibration; Covariance matrix; Maximum likelihood estimation; Multiple signal classification; Phase estimation; Phase noise; Phased arrays; Sensor arrays; Sensor phenomena and characterization; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on