SYSYFeb 23, 2017

Adaptive beamforming method based on recursive maximum correntropy in impulsive noise with alpha-stable process

arXiv:1702.03772h-index: 41
AI Analysis

This work addresses the problem of adaptive beamforming under impulsive noise for signal processing applications, but the improvement is incremental as it extends existing MCC-based methods to the complex domain.

The paper proposes a complex recursive maximum correntropy (CRMC) algorithm for adaptive beamforming in impulsive noise environments, demonstrating improved robustness and convergence without requiring prior noise information.

As a well-established adaptation criterion, the maximum correntropy criterion (MCC) has been receiving increasing attention due to its robust against outliers. In this paper, a new complex recursive maximum correntropy (CRMC) algorithm without any priori information on the noise characteristics, is proposed under the MCC. The proposed algorithm is useful for adaptive beamforming, when the desired signal is contaminated by the impulsive noises. Moreover, the analysis of convergence property of the CRMC algorithm is performed. The results obtained from simulation study establish the effectiveness of this new beamformer.

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