Normalized-Orthogonal Projection Beamforming Amid Heavy-Tailed Impulsive Noise of Unknown Statistics
Hongtao Li, Chen Gu, Xiaohua Zhu · 2011
This paper presents a new normalized orthogonal projection (NOP) beamforming technique, against arbitrary unknown heavy-tailed impulsive noises. To improve the performance of the beamformer amid heavy-tailed impulsive noise of unknown statistics, this new algorithm put the weight vector to the noise subspace based on orthogonal projection principles after the input signal being infinity-norm snapshot-normalized. This NOP beamformer is versatile and robust in any impulsive-noise and non-stationary noise model, in the sense that this beamformer is not tailored specifically to any specific impulsive noise model. This new NOP beamformer has these advantages: (1) needing neither prior information nor estimation of the impulsive noise's effective characteristic exponent's numerical value, (2) applicable to a wider class of heavy-tailed impulsive noises, (3) providing lower sidelobe and (4) offering better interference-rejection. Monte-Carlo simulation results verify the validity and superiority of the proposed algorithm.