Machine learning-assisted lens-loaded cavity response optimization for improved direction-of-arrival estimation

Machine learning-assisted lens-loaded cavity response optimization for improved direction-of-arrival estimation

Abstract This paper presents a millimeter-wave direction of arrival estimation (DoA) technique powered by dynamic aperture optimization. The frequency-diverse medium in this work is a lens-loaded oversized mmWave cavity that hosts quasi-random wave-chaotic radiation modes. The presence of the lens i...

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Bibliographic Details
Main Authors: Muhammad Ali Babar Abbasi, Mobayode O. Akinsolu, Bo Liu, Okan Yurduseven, Vincent F. Fusco, Muhammad Ali Imran
Format: Article
Language:English
Published: Nature Portfolio 2022-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-12011-z

Internet

https://doi.org/10.1038/s41598-022-12011-z

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