A Power-Only Fast Calibration Method for Phased Array Using Convolution Neural Network

doi:10.1109/LAWP.2024.3452268

2024-11-01

PRE

DOI：10.1109/LAWP.2024.3452268

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摘要

En 中文

A power-only fast calibration method for phased array is proposed in this letter. Empowered by the artificial intelligence (AI) techniques, the novel approach significantly reduces the number of required measurements without sacrificing calibration accuracy. To overcome the challenge of acquiring the training data with labels through measurements, we put forward a simple yet effective signal model for phased arrays, facilitating the generation of abundant high-quality training data via numerical calculation alone. A deep neural network model combining real- and complex-valued networks is developed for the implementation of the calibration method. The performance of the proposed method was first examined by numerical simulations and then verified by experiments using a self-developed Ka-band 64-element phased-array. All validation results consistently confirm the efficiency and calibration accuracy of the proposed method.

Keyword:

Calibration

Vectors

Phased arrays

Phase measurement

Feature extraction

Arrays

Training

Array calibration

complex-valued networks

phased array

power-only

期刊

IEEE Antennas and Wireless Propagation Letters

IF:

4.8

论文数:

1.0W

被引数:

2.8W

机构

zhejiang university

学者数:

17.7W

论文数: 12.1W

被引数: 152

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