An effective array beamforming scheme based on branch-and-bound algorithm

In this paper, we propose an effective full array and sparse adaptive beamforming scheme that can be applied for multiple desired signals based on the branch-and-bound algorithm. Adaptive is realized by improved Capon method. At same time, sidelobe constraint added to reduce level. To pointing errors of signals, response phase signal firstly optimized using auxilary variables while keeping amplitude unchanged. The whole design formulated as a convex optimization problem solved addition, beamformer weight vector penalized with modified reweighted ℓ 1 -norm achieve sparsity. Theoretical analysis simulation results show proposed algorithm has lower level, higher SINR, less error than state-of-the-art methods in case single expected signals.