Vol. 11, No 3: 61–70.

Computer Science and Informatics

 2026

Scientific article

UDK 004.021
pdf-version

Anna A. Basalova
bachelor’s degree, Petrozavodsk State University
(Petrozavodsk, Russia),
anna_basalova@mail.ru

Comparative Analysis of Inertial Sensor Filtering Algorithms for Unmanned Surface Vehicle Attitude Estimation

Scientific adviser:
Aleksandr A. Rogov
Reviewer:
Dmitry G. Korzun
Paper submitted on: 09/14/2026;
Accepted on: 09/28/2026;
Published online on: 09/28/2026.
 Abstract. This paper presents a field comparative evaluation of the Extended Kalman Filter (EKF), Mahony, and Madgwick algorithms for attitude estimation on an unmanned catamaran. The novelty of this study is the validation of these filters on an ESP32 microcontroller in real-world conditions on Lake Onega. The experimental methodology comprised static tests and five dynamic sessions. Quantitative results demonstrated that the Mahony filter yielded the lowest mean positioning error (40.07 m), with static yaw drift under 0.18°. These findings are applicable to USV autopilots operating in unstable GPS conditions.
Keywords: inertial sensors, Kalman filter, Mahony filter, Madgwick filter, unmanned surface vehicle attitude estimation, unmanned surface vehicle, GPS-denied navigation, sensor fusion

For citation: Basalova, A. A. Comparative Analysis of Inertial Sensor Filtering Algorithms for Unmanned Surface Vehicle Attitude Estimation. StudArctic forum. 2026, 11 (3): 61–70.

References

Kapirusov M.A. Overview of autonomous navigation methods. International Journal of Information Technologies and Energy Efficiency, 2024, Vol. 9, No. 8(46), pp. 031–038. (In Russ.)

Alonso A.C., García Carro G., et all. Evaluation of magnetometer-less inertial sensors for static spatial orientation estimation. 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), IEEE, May 2025, pp. 1–6. DOI: 10.1109/I2MTC62753.2025.11079213

Almeida T.E.P. de, Monteiro J.R.B.A., et al. Low cost heading sensing system for an autonomous aquatic surface vehicle. 2014 11th IEEE/IAS International Conference on Industry Applications, IEEE, 2014, pp. 1–6. DOI: 10.1109/INDUSCON.2014.7059447

Bryne T.H., Fossen T.I., et all. Attitude and heave estimation for ships using MEMS-based inertial measurements. IFAC-PapersOnLine, 2016, Vol. 49, No. 23, pp. 568–575. DOI: 10.1016/j.ifacol.2016.10.496

Farrell J. Aided navigation: GPS with high rate sensors. New York, McGraw-Hill, 2008. 456 p.

Ludwig S.A., Burnham K.D. Comparison of Euler estimate using extended Kalman filter, Madgwick and Mahony on quadcopter flight data. 2018 International Conference on Unmanned Aircraft Systems (ICUAS), IEEE, 2018, pp. 1236–1241. DOI: 10.1109/ICUAS.2018.8453465

Madgwick S.O.H. An efficient orientation filter for inertial and inertial/magnetic sensor arrays. Bristol, University of Bristol, 2010, 32 p. URL: https://x-io.co.uk/downloads/madgwick_internal_report.pdf (Accessed: 13.05.2026)

Munarto R., Wiryadinata R., Utama D.P. Implementation of AHRS (attitude heading and reference systems) with Madgwick filter as hexapods robot navigation. 2022 International Conference on Informatics Electrical and Electronics (ICIEE), IEEE, Oct. 2022, pp. 1–9. DOI: 10.1109/ICIEE55596.2022.10010044

Simon H., Fehér Á., et al. Comparative analysis of attitude estimation algorithms on embedded systems. 2025 IEEE 19th International Symposium on Applied Computational Intelligence and Informatics (SACI), IEEE, 2025, pp. 31–36. DOI: 10.1109/SACI66288.2025.11030114

Wang M., Gao Y., et all. UAV attitude measurement based on enhanced Mahony complementary filter. 2018 IEEE International Conference on Mechatronics and Automation (ICMA), IEEE, 2018, pp. 545–550. DOI: 10.1109/ICMA.2018.8484522

Zhang S., Yu S., et all. A dual-linear Kalman filter for real-time orientation determination system using low-cost MEMS sensors. Sensors, 2016, Vol. 16, No. 2, pp. 264. DOI: 10.3390/s16020264

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