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Automatic Generalized Loading for Robust Adaptive Beamforming

delete2009-03-01
delete37
PRE
AI
J
Jun Yang *
X
Xiaochuan Ma
C
Chaohuan Hou
Y
Yicong Liu
DOI:10.1109/LSP.2008.2010807delete
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Abstract

Abstract

En 中文
The goal of this letter is to derive robust adaptive beamformers via generalized loading. In the proposed methods, Hermitian matrices are loaded on sample covariance matrix, and this is different from those methods based on the well-known diagonal loading approach. Furthermore, the computation of the loaded matrix is fully automatic, which is scarce in the literature. Numerical examples show that our methods are more robust to errors on array steering vector and sample covariance matrix than other tested parameter-free methods.
Keywords:
Adaptive beamforming
generalized loading
minimum variance beamforming
robust beamforming
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

C
chinese academy of sciences
Scholars:
56.7W
Papers: 45.0W
Citations: 704
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