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

TL;DR

This paper introduces a novel recursive maximum correntropy algorithm for adaptive beamforming in impulsive noise environments, demonstrating robustness and convergence without prior noise information.

Contribution

The paper proposes a new complex recursive MCC algorithm for adaptive beamforming that operates effectively in impulsive noise without prior noise characteristic knowledge.

Findings

The proposed CRMC algorithm outperforms traditional methods in impulsive noise scenarios.

Simulation results confirm the convergence and robustness of the new beamformer.

The method is effective for impulsive noise with alpha-stable process characteristics.

Abstract

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.