Iterative adaptive approach to interference covariance matrix reconstruction for robust adaptive beamforming

作者：Meng, Zhen; Shen, Feng^*; Zhou, Weidong

来源：IET Microwaves Antennas & Propagation, 2018, 12(10): 1704-1708.

DOI：10.1049/iet-map.2017.1125

• array signal processing
• iterative methods
• signal reconstruction
• covariance matrices
• interference (signal)
• adaptive signal processing
• iterative adaptive approach
• robust adaptive beamforming method
• performance losses
• model mismatches
• training sample
• sample covariance matrix
• angular sector reconstruction algorithm
• interference-plus-noise covariance matrix reconstruction
• INCM reconstruction methods
• Capon spectrum estimator
• spatial power spectrum
• power estimates

It is well known that adaptive beamforming methods are susceptible to performance losses in the presence of model mismatches, especially when the training sample is contaminated by the desired signal. Here, in order to thoroughly remove the desired signal from the sample covariance matrix, the authors propose an iterative adaptive approach based on angular sector reconstruction algorithm to reconstruct the interference-plus-noise covariance matrix (INCM). Traditional INCM reconstruction methods are based on the Capon spectrum estimator to obtain the spatial power spectrum. However, the Capon spectrum cannot provide accurate power estimates because it is known to be sensitive to the array calibration error. Inspired by the excellent behaviour of the IAA algorithm, the authors use the IAA spectrum to obtain accurate power estimates which can be used to reconstruct the interference covariance matrix and revise the desired signal steering vector. Simulation results show that the performance of the proposed robust adaptive beamformer outperforms previous works and the output signal-to-interference-plus-noise ratios are close to the optimal values.

• 出版日期2018-8-15
• 单位哈尔滨工程大学