Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19338
Title: Linearly constrained minimum-"Geometric power" adaptive beamforming using logarithmic moments of data containing Heavy-Tailed noise of unknown statistics
Authors: He, J
Liu, Z
Wong, KT 
Keywords: Adaptive arrays
Array signal processing
Beam steering
Focusing
Impulse noise
Parameter estimation
Issue Date: 2007
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Source: IEEE antennas and wireless propagation letters, 2007, v. 6, 910928, p. 600-603 How to cite?
Journal: IEEE Antennas and Wireless Propagation Letters 
Abstract: This letter presents a new adaptive beamforming approach, against arbitrary algebraically tailed impulse noise of otherwise unknown statistics. (This includes all symmetric Q-stable noises with infinite variance or even infinite mean.) This new beamformer iteratively minimizes the "geometric power" of the beamformer's output Y, subject to a prespecified set of linear constraints. This geometric power is defined in terms of the "logarithmic moment" .E{log|Y|}, as an alternative to the customary "fractional lower order moments" (FLOM). This logarithmic-moment beamformer offers these advantages over the FLOM beamformer: 1) simpler computationally in general, 2) needing no prior information nor estimation of the numerical value of the impulse noise's effective characteristic exponent, and 3) applicable to a wider class of heavy-tailed Impulse noises.
URI: http://hdl.handle.net/10397/19338
DOI: 10.1109/LAWP.2007.910928
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