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In practical applications, mismatches between assumed and actual array responses lead to serious degradation of SINR at the array output. In this paper, we propose robust CMA based on the quadratic constraint, which improves the output performance. The quadratic constraint on the weight can provide excellent robustness to signal steering vector mismatches and to random perturbations in sensor parameters...
In practical problems, the constrained least square constant modulus algorithm (LSCMA) can suffer significant performance degradation in the presence of the slight mismatches between the actual and presumed array responses to the desired signal. In this paper, a novel robust constrained LSCMA is proposed based on explicit modeling of uncertainties in the desired signal array response. The proposed...
When adaptive arrays are applied to practical problems, the constrained LSCMA can suffer significant performance degradation in the presence of the mismatch between the actual direction of arrival (DOA) of the signal and the look direction of the beamformers. In this paper, a novel robust constrained LSCMA under signal steering vector mismatches is proposed by using a Bayesian approach, which is robust...
When the array steering vector is precisely known, adaptive beamforming is known to have resolution and interference rejection capability. However, the performance of adaptive beamforming techniques may degrade severely in the presence of mismatches between the assumed array response and the true array response. Similar types of degradation can occur when the signal array response is known exactly,...
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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