A 3-D-printed W-band slotted waveguide array antenna optimized using machine learning

Jinpil Tak, Adnan Kantemur, Yashika Sharma, Hao Xin

Research output: Contribution to journalArticlepeer-review

134 Scopus citations

Abstract

A three-dimensional (3-D) printed W-band slotted waveguide array antenna (SWAA) is proposed. The proposed SWAA consists of three different sections (two horizontal ones and a vertical one) such as a radiating waveguide array with 10 × 10 slots array with an aperture size of 31 mm × 31.4 mm, a coupling waveguide to feed the radiating waveguide array, and a vertical waveguide to feed the coupling waveguide. Machine learning technique based on artificial neural network algorithm is used to optimize the design. The optimized SWAA is fabricated using stereolithography apparatus (SLA) 3-D printing and then is metallized with silver on the inner and outer surfaces by jet metal spraying method. To metallize the inner and outer surfaces of the monolithic structure, nonradiating slots are added on the surface of the designed SWAA. The surface roughness is taken into account by employing the Huray-model methodology in simulation. The SWAA has a 22.5 dBi far-field gain, a-13.5 dB sidelobe level, and 10° half-power beamwidth (HPBW) at 78.7 GHz in measurement.

Original languageEnglish (US)
Article number8416711
Pages (from-to)2008-2012
Number of pages5
JournalIEEE Antennas and Wireless Propagation Letters
Volume17
Issue number11
DOIs
StatePublished - Nov 2018

Keywords

  • 3-D printing
  • Antenna arrays
  • W-band
  • artificial neural network
  • slotted waveguide

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A 3-D-printed W-band slotted waveguide array antenna optimized using machine learning'. Together they form a unique fingerprint.

Cite this