An Adaptive Beamforming Algorithm With Simultaneous Mainlobe Response And Tolerance Sensitivity Constraints
Henry L. Cox · 2005
Adaptive beamforming algorithms sometimes are very sensitive to slight errors in array characteristics. Errors which are uncorrelated from sensor to sensor pass through the beamformer like uncorrelated or spatially white noise. Hence, gain against white noise is a measure of robustness. A new algorithm is presented which includes a quadratic inequality constraint on the array gain against uncorrelated noise. while minimizing output power subject to multiple linear equality constraints. It is shown that a simple scaling of the projection of the weights in a subspace can be used to satisfy the quadratic inequality constraint. This leads to a simple effective robust adaptive beamforming algorithm.