Adaptive beamforming algorithm for subarrays based on coprime array

This paper proposes an adaptive beamforming algorithm based on the subarray technology of coprime array to avoid the occurrence of grating lobes and reduce complexity, in response to the problem of excessive data and computational complexity in processing large array antennas. Firstly, this paper divides the number of subarrays based on the number of elements in the coprime array; Subsequently, weighted compensation is performed within the subarray to compensate for the delay of the internal elements relative to the reference elements; Finally, subarray weighting is performed to enhance the output performance of the sampled signals. Compared with previous works, the proposed algorithm greatly reduces the computational complexity while improving the output performance of the adaptive beamformer at high signal-to-noise ratio. The validity and reliability of the proposed algorithm is verified through simulation experiments.

Authors

Institutions

Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/eit63098.2024.10762283
Primary Topic
Antenna Design and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive beamforming algorithm for subarrays based on coprime array

Bin Ba, Yang Du, Weijia Cui, Long Zhang et al.
Antenna Design and Optimization
article

Adaptive beamforming algorithm for subarrays based on coprime array

Bin Ba, Yang Du, Weijia Cui, Long Zhang, Jin Zhang
article en

Abstract

This paper proposes an adaptive beamforming algorithm based on the subarray technology of coprime array to avoid the occurrence of grating lobes and reduce complexity, in response to the problem of excessive data and computational complexity in processing large array antennas. Firstly, this paper divides the number of subarrays based on the number of elements in the coprime array; Subsequently, weighted compensation is performed within the subarray to compensate for the delay of the internal elements relative to the reference elements; Finally, subarray weighting is performed to enhance the output performance of the sampled signals. Compared with previous works, the proposed algorithm greatly reduces the computational complexity while improving the output performance of the adaptive beamformer at high signal-to-noise ratio. The validity and reliability of the proposed algorithm is verified through simulation experiments.

PLA Information Engineering University (CN)
Openalex Percentile: Top 58%
Antenna Design and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.