scholarly journals High Performance Robust Adaptive Beamforming in the Presence of Array Imperfections

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Wenxing Li ◽  
Xiaojun Mao ◽  
Zhuqun Zhai ◽  
Yingsong Li

A high performance robust beamforming scheme is proposed to combat model mismatch. Our method lies in the novel construction of interference-plus-noise (IPN) covariance matrix. The IPN covariance matrix consists of two parts. The first part is obtained by utilizing the Capon spectrum estimator integrated over a region separated from the direction of the desired signal and the second part is acquired by removing the desired signal component from the sample covariance matrix. Then a weighted summation of these two parts is utilized to reconstruct the IPN matrix. Moreover, a steering vector estimation method based on orthogonal constraint is also proposed. In this method, the presumed steering vector is corrected via orthogonal constraint under the condition where the estimation does not converge to any of the interference steering vectors. To further improve the proposed method in low signal-to-noise ratio (SNR), a hybrid method is proposed by incorporating the diagonal loading method into the IPN matrix reconstruction. Finally, various simulations are performed to demonstrate that the proposed beamformer provides strong robustness against a variety of array mismatches. The output signal-to-interference-plus-noise ratio (SINR) improvement of the beamformer due to the proposed method is significant.

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Pei Chen ◽  
Yongjun Zhao ◽  
Chengcheng Liu

A novel low-complexity robust adaptive beamforming (RAB) technique is proposed in order to overcome the major drawbacks from which the recent reported RAB algorithms suffer, mainly the high computational cost and the requirement for optimization programs. The proposed algorithm estimates the array steering vector (ASV) using a closed-form formula obtained by a subspace-based method and reconstructs the interference-plus-noise (IPN) covariance matrix by utilizing a sampling progress and employing the covariance matrix taper (CMT) technique. Moreover, the proposed beamformer only requires knowledge of the antenna array geometry and prior information of the probable angular sector in which the actual ASV lies. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm and prove that this algorithm can achieve superior performance over the existing RAB methods.


2013 ◽  
Vol 791-793 ◽  
pp. 2092-2095
Author(s):  
Xiao Ke Huang ◽  
Luo Kun Liu ◽  
You Ming Sun ◽  
Jin Jin Yang

Proposed a robust adaptive beamforming algorithm for the beamformers performance degradation in high Signal-to-Noise Ratios (SNRs), which is based on interference covariance matrix reconstruction and steering vector estimation. The simulation results prove the effectiveness.


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