From Global GPS to Local Waypoints: A UTM-Based GPS-IMU Localization Method for VTOL UAV Navigation
DOI:
https://doi.org/10.30871/jaic.v10i2.12391Keywords:
GPS, IMU, Localization, UTM, VTOL UAVAbstract
This study presents a deterministic UTM-based GPS–IMU localization framework for short-range waypoint navigation of a Vertical Take-Off and Landing (VTOL) unmanned aerial vehicle. Unlike conventional GNSS–IMU approaches that rely on tightly coupled probabilistic fusion algorithms, the proposed method emphasizes coordinate transformation efficiency for relative waypoint consistency under open-sky conditions. GPS latitude–longitude data from a standalone u-blox M10 receiver are converted into Universal Transverse Mercator (UTM) coordinates and transformed into a local Cartesian reference frame to enable efficient distance and bearing computation. Heading information is obtained from IMU yaw measurements embedded in the Pixhawk 6C flight controller. Experimental validation was conducted in an open-sky environment using five predefined waypoint positions per trial. Performance was evaluated using Root Mean Square Error (RMSE) and sample standard deviation metrics. The system achieved distance RMSE values of 0.030 m, 0.047 m, and 0.017 m across three scenarios, while bearing RMSE remained within 4–5°, satisfying the predefined benchmark (distance RMSE < 0.1 m; bearing RMSE < 5°). These results reflect short-range relative geometric consistency rather than absolute GNSS positioning accuracy. The findings demonstrate that deterministic UTM-based coordinate transformation combined with GPS–IMU heading estimation provides stable short-range waypoint consistency without requiring additional probabilistic fusion algorithms.
Downloads
References
[1] M. Idrissi, M. Salami, and F. Annaz, “A review of quadrotor unmanned aerial vehicles: Applications, architectural design and control algorithms,” J. Intell. Robot Syst., vol. 104, Art. no. 22, 2022, doi: 10.1007/s10846-021-01527-7.
[2] A. C. Subrata, “Automatic landing and waypoint system berbasis kombinasi GPS dan mesin visi untuk multirotor pada Kontes Robot Terbang Indonesia divisi vertical take off landing,” J. Ilm. Tek. Elektro Komput. dan Inform. (JITEKI), vol. 2, no. 2, pp. 110–122, Dec. 2016, doi: 10.26555/jiteki.v2i2.4896.
[3] C. Chi, X. Zhan, S. Wang, and Y. Zhai, “Enabling robust and accurate navigation for UAVs using real-time GNSS precise point positioning and IMU integration,” Aeronaut. J., vol. 124, no. 1278, pp. 1–22, 2020, doi: 10.1017/aer.2020.80.
[4] Y. S. Wang, X. Zhang, and L. Chen, “UAV sensor data fusion for localization using adaptive multiscale feature matching mechanisms,” Aerospace, vol. 12, no. 12, pp. 1–18, 2025, doi: 10.3390/aerospace12121048.
[5] Y. Chang, Y. Cheng, U. Manzoor, and J. Murray, “A review of UAV autonomous navigation in GPS-denied environments,” Robot. Auton. Syst., vol. 170, Art. no. 104533, 2023, doi: 10.1016/j.robot.2023.104533.
[6] H. Zhang, L. Wang, and J. Li, “Review of AI-based UAV navigation in GPS-denied environments,” in Proc. Int. Conf. Artif. Intell., 2024, pp. 1–8.
[7] W. Jang, M. Cho, H. Lim, and S. Lee, “Vision-based optimal landing guidance law for VTOL UAVs on a moving platform,” Int. J. Aeronaut. Space Sci., vol. 26, pp. 1708–1731, 2025, doi: 10.1007/s42405-024-00825-2.
[8] R. Mahony, V. Kumar, and P. Corke, “Multirotor aerial vehicles: Modeling, estimation, and control,” IEEE Robot. Autom. Mag., vol. 23, no. 2, pp. 20–32, 2016.
[9] S. Bouabdallah, P. Murrieri, and R. Siegwart, “Design and control of quadrotors with application to autonomous flying,” Annu. Rev. Control, vol. 44, pp. 20–32, 2017, doi: 10.1016/j.arcontrol.2017.09.004.
[10] G. Hoffmann et al., “Quadrotor helicopter flight dynamics and control,” in AIAA Guid., Navig., Control Conf., 2016.
[11] L. Meier et al., “PX4: A node-based multithreaded open source robotics framework,” in Proc. IEEE Int. Conf. Robot. Autom. (ICRA), 2018, pp. 1–8.
[12] Y. Zhang et al., “GPS/INS integrated navigation systems: A review,” J. Navig., vol. 70, no. 1, pp. 1–19, 2017, doi: 10.1017/S0373463316000412.
[13] R. Beard and T. McLain, “Guidance, navigation, and control of fixed-wing and multirotor UAVs,” IEEE Control Syst. Mag., vol. 37, no. 2, pp. 33–46, 2017, doi: 10.1109/MCS.2017.2676316.
[14] Y. Sun et al., “Design and implementation of a UAV navigation system based on GPS/IMU integration,” Sensors, vol. 18, no. 10, Art. no. 3416, 2018, doi: 10.3390/s18103416.
[15] M. Ryll, H. H. Bülthoff, and P. R. Giordano, “A novel overactuated quadrotor UAV: Modeling, control, and experimental evaluation,” IEEE Trans. Control Syst. Technol., vol. 29, no. 6, pp. 2568–2581, 2021, doi: 10.1109/TCST.2020.3005857.
[16] C. F. F. Karney, “Algorithms for geodesics,” J. Geodesy, vol. 89, no. 1, pp. 43–55, 2015, doi: 10.1007/s00190-014-0766-0.
[17] Z. Li, S. Bian, Q. Liu, H. Li, C. Chen, and Y. Hu, “Nonzonal expressions of Gauss–Krüger projection in polar regions,” ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., vol. III-4, pp. 11–15, 2016, doi: 10.5194/isprs-annals-III-4-11-2016.
[18] O. Lewicka et al., “Analysis of transformation methods of hydroacoustic and geospatial data,” Remote Sens., vol. 14, no. 7, 2022, doi: 10.3390/rs14071618.
[19] A. Elamin, N. Abdelaziz, and A. El-Rabbany, “A GNSS/INS/LiDAR integration scheme for UAV-based navigation in GNSS-challenging environments,” Sensors, vol. 22, no. 24, Art. no. 9908, 2022, doi: 10.3390/s22249908.
[20] A. Tonini, M. Castelli, J. S. Bates, N. N. N. Lin, and M. Painho, “Visual-inertial method for localizing aerial vehicles in GNSS-denied environments,” Appl. Sci., vol. 14, no. 20, Art. no. 9493, 2024, doi: 10.3390/app14209493.
[21] M. de Berg, J. Snoeyink, and M. van Kreveld, “Waypoint navigation of mobile robots using distance and bearing control,” arXiv preprint arXiv:1803.05447, 2018.
[22] J. Kim, S. Lee, and H. Kim, “Design of waypoint navigation and guidance system for UAV,” Appl. Sci., vol. 10, no. 9, Art. no. 3070, 2020, doi: 10.3390/app10093070.
[23] M. P. Christiansen et al., “Designing and testing a UAV mapping system for accurate pose estimation,” Sensors, vol. 17, no. 12, Art. no. 2703, 2017, doi: 10.3390/s17122703.
[24] Y. Yao et al., “UAV geo-localization dataset and method based on cross-view matching,” Sensors, vol. 24, no. 21, Art. no. 6905, 2024, doi: 10.3390/s24216905.
[25] Y. Yang, “UAV waypoint opportunistic navigation in GNSS-denied environments,” M.S. thesis, Ohio State Univ., Columbus, OH, USA, 2022.
[26] R. S. Wijaya, E. R. Jamzuri, A. Wibisana, J. A. Sinaga, and V. Julanba, “Sensor fusion–based localization for ASV with linear regression optimization,” J. Appl. Inform. Comput., vol. 9, no. 4, pp. 1991–1999, 2023, doi: 10.30871/jaic.v9i4.10048.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ryan Satria Wijaya, Nedia Waty, Nur Rafia Dija
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) ) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
