Robust adaptive beamforming for large-scale arrays
Signal Processing
Robust adaptive beamformers based on worst-case optimization and constraints on magnitude response
IEEE Transactions on Signal Processing
A class of constrained adaptive beamforming algorithms based on uniform linear arrays
IEEE Transactions on Signal Processing
A robust adaptive beamformer based on worst-case semi-definite programming
IEEE Transactions on Signal Processing
Modified projection approach for robust adaptive array beamforming
Signal Processing
Quadratically Constrained Beamforming Robust Against Direction-of-Arrival Mismatch
IEEE Transactions on Signal Processing
On robust Capon beamforming and diagonal loading
IEEE Transactions on Signal Processing
A projection approach for robust adaptive beamforming
IEEE Transactions on Signal Processing
Robust adaptive beamforming for general-rank signal models
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Iterative Robust Minimum Variance Beamforming
IEEE Transactions on Signal Processing
Design of Optimized Radar Codes With a Peak to Average Power Ratio Constraint
IEEE Transactions on Signal Processing
Robust Capon beamforming against large DOA mismatch
Signal Processing
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Adaptive beamformers will degrade in the presence of model mismatch. Because a wider beamwidth has higher ability against steering vector errors, and lower sidelobe levels can improve the robustness against fast moving interferences, in this work an iterative fast Fourier transform (FFT) based adaptive beamformer is proposed with constraints on beamwidth and peak sidelobe level. The adaptive beamforming is transformed to a weighted pattern synthesis problem. This weighted pattern is a product of the array pattern and a weighting function. Because the weighting function has shape peaks at the direction of interferences, it will have nulls in the array pattern at the directions of interferences by reducing the peak sidelobe level of this weighted pattern. A modified iterative FFT algorithm is proposed to synthesize this weighted pattern. Thanks to the efficiency of FFT, the nonconvex problem of power pattern synthesis can be solved efficiently. This method is demonstrated through several simulation examples. The results show the advantages of the proposed method in obtaining high output SINRs against moving target signals and steering vector errors.