Efficient 2D adaptive beamforming algorithm based on sparse array optimisation

In this study, a 2D adaptive beamforming algorithm for sparse array is proposed. Firstly, a signal model based on matrix completion theory for adaptive beamforming in sparse array is established, which is proved to satisfy null space property. Secondly, in order to enhance the performance of reconst...

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Vydáno v:Journal of engineering (Stevenage, England) Ročník 2019; číslo 21; s. 7985 - 7988
Hlavní autoři: Wang, Chaoyu, Zhu, Can, Chen, Chunlin, Li, Hongtao
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 01.11.2019
Wiley
Témata:
accelerated proximal gradient algorithm
adaptive beamforming weight
array signal processing
complete received signal matrix
computational complexity
genetic algorithm
genetic algorithms
gradient methods
IET International Radar Conference (IRC 2018)
interference suppression
matrix algebra
matrix completion theory
signal model
sparse array elements
sparse array optimisation
sparse sampling array
signal model
interference suppression
sparse sampling array
sparse array elements
genetic algorithms
matrix algebra
sparse array optimisation
genetic algorithm
adaptive beamforming weight
accelerated proximal gradient algorithm
gradient methods
matrix completion theory
array signal processing
computational complexity
complete received signal matrix
ISSN:2051-3305, 2051-3305
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Popis
Shrnutí:In this study, a 2D adaptive beamforming algorithm for sparse array is proposed. Firstly, a signal model based on matrix completion theory for adaptive beamforming in sparse array is established, which is proved to satisfy null space property. Secondly, in order to enhance the performance of reconstructing complete received signal matrix, genetic algorithm is used to optimise the sparse sampling array. Thirdly, the accelerated proximal gradient algorithm is adopted to reconstruct the complete received signal matrix. Finally, the adaptive beamforming weight is provided directly to form beam patterns, which can be obtained as a result of reconstructing complete received signal matrix. The proposed method could improve the utilisation rate of the sparse array elements and reduce the computational complexity in interference suppression. Simulation results show the effectiveness of the method.
ISSN:2051-3305
2051-3305
DOI:10.1049/joe.2019.0767