Study of Efficient Robust Adaptive Beamforming Algorithms Based on Shrinkage Techniques

H. Ruan; R. C. de Lamare

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arXiv · 1512.01601

Study of Efficient Robust Adaptive Beamforming Algorithms Based on Shrinkage Techniques

H. Ruan·R. C. de Lamare

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Abstract

This paper proposes low-complexity robust adaptive beamforming (RAB) techniques based on shrinkage methods. We firstly briefly review a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) batch algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is also estimated with a recursive matrix shrinkage method. Then we develop low complexity adaptive robust version of the conjugate gradient (CG) algorithm to both estimate the steering vector mismatch and update the beamforming weights. A computational complexity study of the proposed and existing algorithms is carried out. Simulations are conducted in local scattering scenarios and comparisons to existing RAB techniques are provided.

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H. Ruan, R. C. de Lamare. 2015-12-05. Study of Efficient Robust Adaptive Beamforming Algorithms Based on Shrinkage Techniques. https://arxiv.org/abs/1512.01601

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