Open AccessFast and robust adaptive beamforming method based on l 1‐norm constraint for large array
Author(s) -
Xie Hu,
Feng DaZheng,
Yu HongBo
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2014.2919
Subject(s) - adaptive beamformer , constraint (computer aided design) , norm (philosophy) , weight , computational complexity theory , algorithm , beamforming , robustness (evolution) , mathematical optimization , control theory (sociology) , mathematics , computer science , artificial intelligence , telecommunications , biochemistry , chemistry , geometry , control (management) , lie algebra , political science , pure mathematics , law , gene
A robust adaptive beamformer (BF) with low computational complexity is proposed, where the adaptive weight is formulated as a linear combination of the training samples vectors and the target steering vector in the high interferences‐to‐noise ratio (INR) case. When the number of samples is greater than that of the interferences, an l 1‐norm constraint is imposed on the combinational vector to force its sparsity. Simulation results indicate that the proposed algorithm outperforms some classical robust BFs.