A Robust Adaptive Beamforming Algorithm for Mismatch and Impulsive Noise Circumstance

This letter provides a solution to a robust adaptive beamformer used in remote sensing systems under the effect of two factors: i) the impulsive noise satisfying Gaussian mixture distribution and ii) unknown model mismatches, such as look direction errors, sensor location perturbations, etc. First, a beamformer output-based cost function is designed to effectively suppress the influence of impulsive noise. Second, the weight vector of the beamformer is regularized through norm constraints to reduce the impact of model mismatches. Furthermore, an efficient iterative scheme is established to quickly minimize the designed cost function based on their properties, and a robust adaptive beamformer can be obtained. Finally, computer simulations are presented to demonstrate the robust performance and fast convergence of the novel algorithm in the presence of impulsive noise and model mismatches.