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

TL;DR

This paper introduces a robust, low-complexity beam tracking method for UAV communications using monopulse signals and an extended Kalman filter, improving reliability and stability over traditional schemes.

Contribution

It proposes a novel beam tracking scheme based on monopulse signals and EKF, addressing mobility and disconnection issues with enhanced robustness and reduced complexity.

Findings

The proposed scheme achieves stable UAV tracking with bounded mean square error.

It outperforms conventional methods in robustness and complexity.

The scheme effectively detects beam disconnection in real-time.

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.