Paper Info
Title
Robust adaptive beamforming and steering vector estimation in partly calibrated sensor arrays: A structured uncertainty approach
Abstract
Two new approaches to adaptive beamforming in sparse subarray-based sensor arrays are proposed. Each subarray is assumed to be well calibrated but the intersubarray gain and/or phase mismatches are assumed to remain unknown or imperfectly known. Our first approach is based on a worst-case beamformer design that, unlike the existing worst-case designs, exploits a structured ellipsoidal uncertainty model for the signal steering vector. Our second approach exploits the idea of estimating the signal steering vector by maximizing the output power of the minimum variance beamformer. Several modifications of our second approach are developed for the cases of gain-and-phase and phase-only intersubarray distortions.
Year
DOI
Venue
2010
10.1109/ICASSP.2010.5496308
ICASSP
Keywords
Field
DocType
ellipsoidal uncertainty model,gain-and-phase intersubarray distortions,worst-case beamformer design,sparse subarray-based sensor arrays,steering vector estimation,worst-case designs,minimum variance beamformer,structured uncertainty,array signal processing,phase-only intersubarray distortions,robust adaptive beamforming,partly calibrated arrays,signal steering vector,convex optimization,sensor arrays,adaptive beamforming,robustness,power generation,signal to noise ratio,minimum variance,interference,uncertainty,phase distortion,calibration,sensor array
Minimum-variance unbiased estimator,Ellipsoid,Mathematical optimization,Adaptive beamformer,Computer science,Control theory,Signal-to-noise ratio,Robustness (computer science),Phase distortion,Interference (wave propagation),Convex optimization
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4244-4296-6
978-1-4244-4296-6
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Lei Lei1172.52
Joni Polili Lie2637.43
alex b gershman392066.97
Chong Meng Samson See417519.41