DocumentCode
902704
Title
Rank reduction direction-of-arrival estimators with an improved robustness against subarray orientation errors
Author
Elkader, Sherif Abd ; Gershman, Alex B. ; Wong, Kon Max
Author_Institution
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont., Canada
Volume
54
Issue
5
fYear
2006
fDate
5/1/2006 12:00:00 AM
Firstpage
1951
Lastpage
1955
Abstract
The problem of signal direction-of-arrival (DOA) estimation in partly calibrated arrays composed of multiple subarrays with unknown intersubarray parameters and imperfectly known subarray orientations is studied. The recently developed spectral and root versions of the rank reduction estimator (RARE) are applicable to scenarios where no intersubarray calibration is available, but unfortunately, these algorithms are very sensitive to subarray orientation errors. Therefore, the conventional RARE algorithms can be applied to partly calibrated arrays with subarray orientation errors only if these errors are negligibly small. In this correspondence, a new robust modification of the RARE algorithm with a reduced sensitivity to subarray misorientations is proposed, and expressions for the corresponding stochastic Crame´r-Rao bound (CRB) are derived. The performance of our robust RARE algorithm is demonstrated to be close to this bound in the case of moderate subarray orientation errors.
Keywords
array signal processing; direction-of-arrival estimation; matrix algebra; DOA estimation; RARE algorithm; rank reduction estimator; signal direction-of-arrival estimation; stochastic Cramer-Rao bound; subarray orientation factors; Apertures; Calibration; Costs; Direction of arrival estimation; Geometry; Hardware; Robustness; Sensor arrays; Signal processing algorithms; Stochastic processes; Direction-of-arrival (DOA) estimation; partly calibrated arrays; rank reduction estimator (RARE);
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2006.872321
Filename
1621426
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