An Effective Antenna Pattern Reconstruction Method for Planar Near-Field Measurement System

Zheng, Junhao, Chen, Xiaoming and Huang, Yi ORCID: 0000-0001-7774-1024 (2022) An Effective Antenna Pattern Reconstruction Method for Planar Near-Field Measurement System. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 71. pp. 1-12.

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Official URL: http://dx.doi.org/10.1109/tim.2022.3193194

Abstract

This article presents a method of antenna radiation pattern reconstruction for the planar near-field measurement system. The proposed method uses clustering analysis and Voronoi cell classification to realize reasonable regional interpolation according to the data characteristics of a small number of initial samples, leading to an expansion of the amount of effective data in the initial array. Meanwhile, the Gerchberg-Papoulis (GP) algorithm is used to reduce the truncation errors of the interpolated planar near-field data, and consequently improve the overall reconstruction accuracy. The proposed method can effectively reduce the number of initial sampling points and the planar near-field scanning time of the measurement process. Besides, it can be seen from the simulation and measurement results that the planar near-field data processed by the clustering interpolation and GP algorithm can effectively enhance the reconstruction accuracy of the far-field pattern of the antenna under test (AUT).

Item Type:	Article
Uncontrolled Keywords:	Antenna measurements, Area measurement, Clustering interpolation, Gerchberg-Papoulis (GP) algorithm, Interpolation, pattern reconstruction, planar near-field measurement, Reconstruction algorithms, Reliability, Sampling methods, Time measurement, Voronoi tessellation
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	02 Sep 2022 10:21
Last Modified:	17 Mar 2024 14:49
DOI:	10.1109/TIM.2022.3193194
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3163171