Beam Tracking Algorithm for UAV Communications Using Kalman Filter

Ha Lim Song; Young Chai Ko; Jungil Cho; Chanho Hwang

doi:10.1109/ICTC49870.2020.9289586

Beam Tracking Algorithm for UAV Communications Using Kalman Filter

Ha Lim Song, Young Chai Ko, Jungil Cho, Chanho Hwang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

To support moving users, stations, or relays in UAV assisted communication, beam tracking is an essential technology. Considering the movements and aerial perturbations of UAV, consistent beam tracking is a challenging problem. To address this problem, we propose an efficient Kalman filter (KF) based beam tracking scheme, which exploits monopulse signal as a measurement model. It can estimate the angular parameter with an accurate update phase. The conventional schemes use the beamformed signal as the measurement model, but the beamformed signal of measurement is ineligible to the KF system. Therefore, we show that the proposed scheme with a novel measurement is appropriate for the tracking scenarios and outperforms conventional schemes.

Original language	English
Title of host publication	ICTC 2020 - 11th International Conference on ICT Convergence
Subtitle of host publication	Data, Network, and AI in the Age of Untact
Publisher	IEEE Computer Society
Pages	1101-1104
Number of pages	4
ISBN (Electronic)	9781728167589
DOIs	https://doi.org/10.1109/ICTC49870.2020.9289586
Publication status	Published - 2020 Oct 21
Event	11th International Conference on Information and Communication Technology Convergence, ICTC 2020 - Jeju Island, Korea, Republic of Duration: 2020 Oct 21 → 2020 Oct 23

Publication series

Name	International Conference on ICT Convergence
Volume	2020-October
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	11th International Conference on Information and Communication Technology Convergence, ICTC 2020
Country/Territory	Korea, Republic of
City	Jeju Island
Period	20/10/21 → 20/10/23

Keywords

Beam Tracking
Beamforming
Extended Kalman filter
Kalman filter
Monopulse signal
UAV communication

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications

Access to Document

10.1109/ICTC49870.2020.9289586

Cite this

Song, H. L., Ko, Y. C., Cho, J., & Hwang, C. (2020). Beam Tracking Algorithm for UAV Communications Using Kalman Filter. In ICTC 2020 - 11th International Conference on ICT Convergence: Data, Network, and AI in the Age of Untact (pp. 1101-1104). [9289586] (International Conference on ICT Convergence; Vol. 2020-October). IEEE Computer Society. https://doi.org/10.1109/ICTC49870.2020.9289586

Beam Tracking Algorithm for UAV Communications Using Kalman Filter. / Song, Ha Lim; Ko, Young Chai; Cho, Jungil et al.

ICTC 2020 - 11th International Conference on ICT Convergence: Data, Network, and AI in the Age of Untact. IEEE Computer Society, 2020. p. 1101-1104 9289586 (International Conference on ICT Convergence; Vol. 2020-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Song, HL, Ko, YC, Cho, J & Hwang, C 2020, Beam Tracking Algorithm for UAV Communications Using Kalman Filter. in ICTC 2020 - 11th International Conference on ICT Convergence: Data, Network, and AI in the Age of Untact., 9289586, International Conference on ICT Convergence, vol. 2020-October, IEEE Computer Society, pp. 1101-1104, 11th International Conference on Information and Communication Technology Convergence, ICTC 2020, Jeju Island, Korea, Republic of, 20/10/21. https://doi.org/10.1109/ICTC49870.2020.9289586

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title = "Beam Tracking Algorithm for UAV Communications Using Kalman Filter",

abstract = "To support moving users, stations, or relays in UAV assisted communication, beam tracking is an essential technology. Considering the movements and aerial perturbations of UAV, consistent beam tracking is a challenging problem. To address this problem, we propose an efficient Kalman filter (KF) based beam tracking scheme, which exploits monopulse signal as a measurement model. It can estimate the angular parameter with an accurate update phase. The conventional schemes use the beamformed signal as the measurement model, but the beamformed signal of measurement is ineligible to the KF system. Therefore, we show that the proposed scheme with a novel measurement is appropriate for the tracking scenarios and outperforms conventional schemes.",

keywords = "Beam Tracking, Beamforming, Extended Kalman filter, Kalman filter, Monopulse signal, UAV communication",

author = "Song, {Ha Lim} and Ko, {Young Chai} and Jungil Cho and Chanho Hwang",

note = "Funding Information: This work was supported by a grant-in-aid of HANWHA SYSTEMS. Publisher Copyright: {\textcopyright} 2020 IEEE.; 11th International Conference on Information and Communication Technology Convergence, ICTC 2020 ; Conference date: 21-10-2020 Through 23-10-2020",

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N2 - To support moving users, stations, or relays in UAV assisted communication, beam tracking is an essential technology. Considering the movements and aerial perturbations of UAV, consistent beam tracking is a challenging problem. To address this problem, we propose an efficient Kalman filter (KF) based beam tracking scheme, which exploits monopulse signal as a measurement model. It can estimate the angular parameter with an accurate update phase. The conventional schemes use the beamformed signal as the measurement model, but the beamformed signal of measurement is ineligible to the KF system. Therefore, we show that the proposed scheme with a novel measurement is appropriate for the tracking scenarios and outperforms conventional schemes.

AB - To support moving users, stations, or relays in UAV assisted communication, beam tracking is an essential technology. Considering the movements and aerial perturbations of UAV, consistent beam tracking is a challenging problem. To address this problem, we propose an efficient Kalman filter (KF) based beam tracking scheme, which exploits monopulse signal as a measurement model. It can estimate the angular parameter with an accurate update phase. The conventional schemes use the beamformed signal as the measurement model, but the beamformed signal of measurement is ineligible to the KF system. Therefore, we show that the proposed scheme with a novel measurement is appropriate for the tracking scenarios and outperforms conventional schemes.

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KW - Beamforming

KW - Extended Kalman filter

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Beam Tracking Algorithm for UAV Communications Using Kalman Filter

Abstract

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Keywords

ASJC Scopus subject areas

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