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A novel robust least squares constant modulus algorithm (LSCMA) is proposed for blind adaptive beamforming, which is based on explicit modeling of uncertainty in the desired signal array. To improve robustness, the weight vector is optimized to involve minimization of cost function, while imposing the oblique projection constraint on the weight vector and maintaining a distortionless response for...
The performances of the conventional adaptive beamforming algorithms degrade severely in the presence of even slight mismatches between the actual and presumed array responses to the desired signal. Similar types of degradation can occur when the signal array response is known exactly, but the training sample size is small. In this paper, based on explicit modeling of uncertainties in the desired...
When applying adaptive arrays to actualities, the performance of existing adaptive array algorithms is known to degrade substantially because of the slight mismatch between actual and presumed array responses to the desired signal. In this paper, a novel robust adaptive beamforming algorithm under directional uncertainty is therefore proposed using a Bayesian approach to respond to the current environment...
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