<FONT face=Verdana>This paper presents a new minimum mean squared “normalized-error” (MMSNE) beamforming technique

against arbitrary unknown heavy-tailed impulsive noises. This new beamformer aims to minimize the “normalized error” between the desired signal and the the beamformer’s output. This normalized error is defined in terms of the instantaneously adaptive infinity-norm snapshot-normalized data. This new MMSNE beamformer outperforms the fractional lower order moments (FLOM)-beamformer with these advantages: (1) simpler computationally with a closed-form solution

(2) needing no prior information nor estimation of the impulsive noise’s effective characteristic exponent’s numerical value

(3) applicable to a wider class of heavy-tailed impulsive noises

(4) providing lower estimation error

and (5) offering better interference-rejection.