A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems

J. S. Jensen, K. Buchanan, J. F. Chamberland, Gregory Huff

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

Abstract

This work proposes a computer vision-based framework for analyzing and synthesizing the collaborative radiation behavior from swarming clusters of intelligent systems. Radiating sensor nodes with inertial measurement units and optical identification features represent the networked cluster of radiators. These create a set of object-distinguishable nodes on a reticulating platform capable of arbitrary spatial distributions. Node discovery and tracking algorithms based on open-source computer vision libraries use image and depth-of-field information from multi-spectral cameras. These locate nodes and their volumetric distribution within the cluster. An automated system then derives the weighted phases for collaborative beamforming from the resulting nodal distribution. Measured and simulated radiation patterns are gathered and compared to demonstrate the capability and accuracy of the proposed framework and to explore its usability in swarm applications.

Original languageEnglish (US)
Title of host publication2017 IEEE Radar Conference, RadarConf 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages118-122
Number of pages5
ISBN (Electronic)9781467388238
DOIs
StatePublished - Jun 7 2017
Event2017 IEEE Radar Conference, RadarConf 2017 - Seattle, United States
Duration: May 8 2017May 12 2017

Publication series

Name2017 IEEE Radar Conference, RadarConf 2017

Other

Other2017 IEEE Radar Conference, RadarConf 2017
CountryUnited States
CitySeattle
Period5/8/175/12/17

Fingerprint

swarming
beamforming
computer vision
Intelligent systems
Beamforming
Computer vision
Units of measurement
Radiators
synthesis
Sensor nodes
Spatial distribution
Cameras
radiators
radiation
Radiation
spatial distribution
platforms
cameras
sensors

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Instrumentation

Cite this

Jensen, J. S., Buchanan, K., Chamberland, J. F., & Huff, G. (2017). A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems. In 2017 IEEE Radar Conference, RadarConf 2017 (pp. 118-122). [7944182] (2017 IEEE Radar Conference, RadarConf 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RADAR.2017.7944182
Jensen, J. S. ; Buchanan, K. ; Chamberland, J. F. ; Huff, Gregory. / A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems. 2017 IEEE Radar Conference, RadarConf 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 118-122 (2017 IEEE Radar Conference, RadarConf 2017).
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Jensen, JS, Buchanan, K, Chamberland, JF & Huff, G 2017, A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems. in 2017 IEEE Radar Conference, RadarConf 2017., 7944182, 2017 IEEE Radar Conference, RadarConf 2017, Institute of Electrical and Electronics Engineers Inc., pp. 118-122, 2017 IEEE Radar Conference, RadarConf 2017, Seattle, United States, 5/8/17. https://doi.org/10.1109/RADAR.2017.7944182

A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems. / Jensen, J. S.; Buchanan, K.; Chamberland, J. F.; Huff, Gregory.

2017 IEEE Radar Conference, RadarConf 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 118-122 7944182 (2017 IEEE Radar Conference, RadarConf 2017).

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

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Jensen JS, Buchanan K, Chamberland JF, Huff G. A computer vision-based framework for the synthesis and analysis of beamforming behavior in swarming intelligent systems. In 2017 IEEE Radar Conference, RadarConf 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 118-122. 7944182. (2017 IEEE Radar Conference, RadarConf 2017). https://doi.org/10.1109/RADAR.2017.7944182