Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction

Jingqing Yang; Xuancheng You; Baoli Ma; Lixia Yan

doi:10.1007/978-981-95-6813-0_44

Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction

Jingqing Yang
, Xuancheng You
, Baoli Ma^*
, Lixia Yan

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Beihang University
Tsinghua University

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

Abstract

This paper presents a cooperative positioning method for multiple unmanned aerial vehicles (UAVs) based on yaw angle correction. As UAVs play an increasingly critical role in the expanding low-altitude airspace economy, achieving accurate and cost-effective localization remains a significant challenge. The proposed approach enhances positioning accuracy by utilizing inter-UAV relative ranging and cooperative localization, with a focus on correcting yaw angle errors. Each UAV is equipped with an inertial measurement unit (IMU) and an ultra-wideband (UWB) ranging module. IMU data is denoised using both low-pass and Kalman filters. Yaw angles are estimated from variations in relative distances, leading to a nonlinear system solved using the least squares method and the Limited-memory Broyden-Fletcher-Goldfarb-Shanno with Bounds (L-BFGS-B) algorithm. Simulation results under constant-altitude flight conditions demonstrate that the method significantly improves positioning accuracy, offering a practical and low-cost solution for inertial navigation.

Original language	English
Title of host publication	Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I
Editors	Yingmin Jia, Yang Liu, Weicun Zhang, Yongling Fu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	446-455
Number of pages	10
ISBN (Print)	9789819568123
DOIs	https://doi.org/10.1007/978-981-95-6813-0_44
State	Published - 2026
Event	21st Chinese Intelligent Systems Conference, CISC 2025 - Beijing, China Duration: 25 Oct 2025 → 26 Oct 2025

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1545 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	21st Chinese Intelligent Systems Conference, CISC 2025
Country/Territory	China
City	Beijing
Period	25/10/25 → 26/10/25

Keywords

Cooperative positioning
L-BFGS-B Algorithm
UAV navigation

Access to Document

10.1007/978-981-95-6813-0_44

Cite this

Yang, J., You, X., Ma, B., & Yan, L. (2026). Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction. In Y. Jia, Y. Liu, W. Zhang, & Y. Fu (Eds.), Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I (pp. 446-455). (Lecture Notes in Electrical Engineering; Vol. 1545 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-95-6813-0_44

Yang, Jingqing ; You, Xuancheng ; Ma, Baoli et al. / Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction. Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I. editor / Yingmin Jia ; Yang Liu ; Weicun Zhang ; Yongling Fu. Springer Science and Business Media Deutschland GmbH, 2026. pp. 446-455 (Lecture Notes in Electrical Engineering).

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title = "Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction",

abstract = "This paper presents a cooperative positioning method for multiple unmanned aerial vehicles (UAVs) based on yaw angle correction. As UAVs play an increasingly critical role in the expanding low-altitude airspace economy, achieving accurate and cost-effective localization remains a significant challenge. The proposed approach enhances positioning accuracy by utilizing inter-UAV relative ranging and cooperative localization, with a focus on correcting yaw angle errors. Each UAV is equipped with an inertial measurement unit (IMU) and an ultra-wideband (UWB) ranging module. IMU data is denoised using both low-pass and Kalman filters. Yaw angles are estimated from variations in relative distances, leading to a nonlinear system solved using the least squares method and the Limited-memory Broyden-Fletcher-Goldfarb-Shanno with Bounds (L-BFGS-B) algorithm. Simulation results under constant-altitude flight conditions demonstrate that the method significantly improves positioning accuracy, offering a practical and low-cost solution for inertial navigation.",

keywords = "Cooperative positioning, L-BFGS-B Algorithm, UAV navigation",

author = "Jingqing Yang and Xuancheng You and Baoli Ma and Lixia Yan",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.; 21st Chinese Intelligent Systems Conference, CISC 2025 ; Conference date: 25-10-2025 Through 26-10-2025",

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doi = "10.1007/978-981-95-6813-0\_44",

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Yang, J, You, X, Ma, B & Yan, L 2026, Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction. in Y Jia, Y Liu, W Zhang & Y Fu (eds), Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I. Lecture Notes in Electrical Engineering, vol. 1545 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 446-455, 21st Chinese Intelligent Systems Conference, CISC 2025, Beijing, China, 25/10/25. https://doi.org/10.1007/978-981-95-6813-0_44

Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction. / Yang, Jingqing; You, Xuancheng; Ma, Baoli et al.
Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I. ed. / Yingmin Jia; Yang Liu; Weicun Zhang; Yongling Fu. Springer Science and Business Media Deutschland GmbH, 2026. p. 446-455 (Lecture Notes in Electrical Engineering; Vol. 1545 LNEE).

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

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N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.

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AB - This paper presents a cooperative positioning method for multiple unmanned aerial vehicles (UAVs) based on yaw angle correction. As UAVs play an increasingly critical role in the expanding low-altitude airspace economy, achieving accurate and cost-effective localization remains a significant challenge. The proposed approach enhances positioning accuracy by utilizing inter-UAV relative ranging and cooperative localization, with a focus on correcting yaw angle errors. Each UAV is equipped with an inertial measurement unit (IMU) and an ultra-wideband (UWB) ranging module. IMU data is denoised using both low-pass and Kalman filters. Yaw angles are estimated from variations in relative distances, leading to a nonlinear system solved using the least squares method and the Limited-memory Broyden-Fletcher-Goldfarb-Shanno with Bounds (L-BFGS-B) algorithm. Simulation results under constant-altitude flight conditions demonstrate that the method significantly improves positioning accuracy, offering a practical and low-cost solution for inertial navigation.

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Yang J, You X, Ma B, Yan L. Cooperative Positioning Strategy for Multiple Unmanned Aerial Vehicles Based on Yaw Angle Correction. In Jia Y, Liu Y, Zhang W, Fu Y, editors, Proceedings of 2025 Chinese Intelligent Systems Conference - Volume I. Springer Science and Business Media Deutschland GmbH. 2026. p. 446-455. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-95-6813-0_44