Topology Optimization of RF GRIN Lenses

Eric B. Whiting, Sawyer D. Campbell, Jingwei Xu, Pingjuan L. Werner, Douglas H. Werner, Jeremy A. Bossard, John P. Barrett, Joshua W. Withrow, Lockheed Martin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is great interest in designing broadband GRadient INdex (GRIN) lenses due to their ability to improve the gain of an antenna over a wide frequency range. However, conventional approaches (e.g., transformation optics) are either difficult to realize due to the required material properties or yield suboptimal performance. Better performance can be achieved by implementing a true inverse-design (optimization) procedure which allows the lens permittivity to vary in a nearly-arbitrary manner. To this end, an adjoint-based topology optimization method is employed which can calculate gradients for an arbitrary number of design variables with only two full-wave simulations. This method is extremely versatile and can be used in conjunction with any arbitrary source, lens shape, and permittivity range to quickly find the best performing designs.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages101-102
Number of pages2
ISBN (Electronic)9781728166704
DOIs
StatePublished - Jul 5 2020
Event2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Virtually, Toronto, Canada
Duration: Jul 5 2020Jul 10 2020

Publication series

Name2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020 - Proceedings

Conference

Conference2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, IEEECONF 2020
CountryCanada
CityVirtually, Toronto
Period7/5/207/10/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Instrumentation

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