科研之友
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摘要
Signal steering vector (SV) error can cause desired signal cancellation in adaptive beamforming. A covariance fitting based robust Capon beamforming (CFRCB) has been developed to solve this problem. Such a solution cannot be expressed in a closed form and its performance is highly affected by the initial value of SV error norm bound. In this paper, we propose an approximate closed-form expression of CFRCB, then develop two novel beamformers based on iterative implementation of this closed-form expression. Theoretical analysis and simulation results indicate that these beamformers improve in performance with every iterative step and converge to a stabilized solution. In addition, they perform well through a wide range of initial SV errors norm bound range, are easily implemented and computationally efficient. We also present a number of numerical examples comparing the proposed beamformers with similar classical beamformers.
