Robust and Low Complexity Beam Tracking with Monopulse Signal for UAV ommunications

Ha Lim Song, Young Chai Ko

Research output: Contribution to journalArticlepeer-review

Abstract

UAV communications based on an antenna array entail a beam tracking technology for reliable link acquisition. Unlike conventional cellular communication, beam tracking in UAV communication addresses new issues such as mobility and abrupt channel disconnection from UAV's perturbation. To deal with these issues, we propose a beam tracking scheme based on extended Kalman filter (EKF) using a monopulse signal, which can provide (1) higher robustness by offering a reliable link in the estimated spatial direction and (2) lower complexity compared with the existing conventional beam tracking schemes. We point out the limitations of using a beamformed signal as a measurement model for a Kalman filter (KF) based scheme and instead utilize the monopulse signal as a more plausible model. For the performance evaluation, we derive the upper bound of the mean square error for spatial angle estimation of UAV and confirm that the proposed scheme is stable with a certain bounded error. We also show from various simulations that the proposed scheme can efficiently track UAV and detect beam disconnection every time frame using a beamformed signal.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Adaptation models
  • Array signal processing
  • Beam tracking
  • beamforming
  • Complexity theory
  • Covariance matrices
  • extended Kalman filter
  • Kalman filter
  • Kalman filters
  • Mean square error methods
  • monopulse signal
  • UAV communication
  • Unmanned aerial vehicles

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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