TY - GEN
T1 - On direction finding with unknown noise covariance
AU - Friedlander, Benjamin
AU - Weiss, Anthony J.
N1 - Publisher Copyright:
© 1995 IEEE.
PY - 1994
Y1 - 1994
N2 - A class of direction finding methods which operate in the presence of correlated noise with an unknown covariance matrix is presented. The approach is based on joint estimation of the directions of arrival and the parameters of a model for the noise covariance matrix, using a maximum likelihood estimator, its suboptimal version or other methods. Formulas for evaluating the maximal number of identifiable noise parameters are also derived. Using the Cramer Rao bound we study the degradation in DOA estimation accuracy due to the estimation of the noise parameters.
AB - A class of direction finding methods which operate in the presence of correlated noise with an unknown covariance matrix is presented. The approach is based on joint estimation of the directions of arrival and the parameters of a model for the noise covariance matrix, using a maximum likelihood estimator, its suboptimal version or other methods. Formulas for evaluating the maximal number of identifiable noise parameters are also derived. Using the Cramer Rao bound we study the degradation in DOA estimation accuracy due to the estimation of the noise parameters.
UR - http://www.scopus.com/inward/record.url?scp=84876573176&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.1994.471567
DO - 10.1109/ACSSC.1994.471567
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AN - SCOPUS:84876573176
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 780
EP - 784
BT - Conference Record - 28th Asilomar Conference on Signals, Systems and Computers, ACSSC 1994
PB - IEEE Computer Society
T2 - 28th Asilomar Conference on Signals, Systems and Computers, ACSSC 1994
Y2 - 31 October 1994 through 2 November 1994
ER -