An Investigation of Geolocation-Aware Beamforming Algorithms for Swarming UAVs Conference Paper

abstract

• 2017 IEEE. Beamforming algorithms for UAV swarms are investigated. The swarm is modeled as a morphing volumetric random array and it is assumed that each element is enabled with orientation awareness. These algorithms are examined to improve the side lobe level for swarms operating as sparse arrays with small numbers of agents or large inter-agent distances. These are also examined to enable more complex beamforming operations for heterogeneous swarms composed of agents with different radiation patterns and/or polarizations. Simulated results based on amplitude tapering algorithms are presented to illustrate the concept, but experimental campaigns have demonstrated the utility of orientation awareness and its ability to provide side information that can enable complex beamforming operations.

name of conference

• 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting

authors

• Chamberland-Tremblay, Jean-Francois

published proceedings

• 2017 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION & USNC/URSI NATIONAL RADIO SCIENCE MEETING

author list (cited authors)

• Yeh, S., Chamberland, J., & Huff, G. H.

citation count

• 12

complete list of authors

• Yeh, Shihyuan||Chamberland, Jean-Francois||Huff, Gregory H

publication date

• January 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• AP-S International Symposium (Digest) (IEEE Antennas and Propagation Society)  Journal

keywords

• Machine Learning Algorithms
• Random Arrays
• Swarms
• Uavs

Digital Object Identifier (DOI)

• 10.1109/apusncursinrsm.2017.8072363

International Standard Book Number (ISBN) 13

• 9781538632840

start page

• 641

end page

• 642

volume

• 2017-January

URL

• http://dx.doi.org/10.1109/apusncursinrsm.2017.8072363