Enhanced Matching for Electrically Small Antennas and Arrays with Machine Learning
Abstract
Approved for Public Release Enhanced Matching for Electrically Small Antennas and Arrays with Machine Learning Abstract: DD-03: Information Superiority, Technical POC: Karen Smith This program will address several areas of considerable interest in spectrum operations for Naval platforms: electrically small antennas, phased arrays, and antenna interaction with the local environment. These considerations will be examined and antenna function will be modified to best support the mission and impact for electronic warfare (EW) and signal intelligence (SIGINT) operations. The research effort for this program will quantify and explore the application of machine learning (ML) to support improved antenna match characteristics and the potential for new solutions to support mission objectives which may include spectrum monitoring, target detection, tracking, fire-control and more. Operation in the HF/VHF bands often requires the use of electrically small antennas due to the low frequency and resulting long wavelengths. The resulting match between the antenna and the driving electronics is often narrowband and not dynamic with respect to antenna location or its operation. Improved input to the match solution for an antenna is expected to better balance improved power transfer and other potentially competing objectives. This program is structured to support a large group of undergraduate researchers and to develop these students’ interest in pursuing employment or graduate education in spectrum operations. The students will work in two groups supporting machine learning and antennas and will combine their efforts in the second and third year. They will perform analysis, prototype construction, computational and measurement roles throughout the program. The program will invigorate fading university interest in electromagnetics applied to EW, radar and communications which are pervasive in the Navy, particularly in the High Frequency (HF) and Very High Frequency (VHF) bands.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 11, 2025
- Source ID
- N001742310020
Entities
People
- Bradley Davis
Organizations
- United States Navy
- Virginia Tech