Wideband corrugated horn design based on machine learning technique
Faculty Advisor
Date
2025
Keywords
corrugated horn antenna, learning data set, machine learning, simulation tools
Abstract (summary)
Corrugated horn antennas are essential in satellite and space communication systems due to their wide bandwidth, low cross-polarization, low side lobes, and excellent return loss. In this paper, several machine learning algorithms are used and trained on CST Microwave Studio data to predict antenna design parameters. The result values achieve a wideband response below 10 dB and a gain error within ±2dBi. These methods offer an efficient initial point for antenna design and reduce development time.
Publication Information
DOI
Notes
Presented on July 21, 2025, at the IEEE 20th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM), in St. John's, Newfoundland, Canada.
Item Type
Presentation
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