Tilt-Induced Error Compensation with Vision-Based Method for Polarization Navigation
Source abstract
Abstract
To rectify significant heading calculation errors in polarized light navigation for unmanned aerial vehicles (UAVs) under tilted states, this paper proposes a method for compensating horizontal attitude angles based on horizon detection. First, a defogging enhancement algorithm that integrates Retinex theory with dark channel prior is adopted to improve image quality in low-illumination and hazy environments. Second, a dynamic threshold segmentation method in the HSV color space (Hue, Saturation, and Value) is proposed for robust horizon region extraction, combined with an improved adaptive bilateral filtering Canny operator for edge detection, aimed at balancing detail preservation and noise suppression. Then, the progressive probabilistic Hough transform is used to efficiently extract parameters of the horizon line. The calculated horizontal attitude angles are utilized to convert the body frame to the navigation frame, achieving compensation for polarization orientation errors. Onboard experiments demonstrate that the horizontal attitude angle estimation error remains within 0.3°, and the heading accuracy after compensation is improved by approximately 77.4% relative to uncompensated heading accuracy, thereby validating the effectiveness of the proposed algorithm.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotics and Sensor-Based Localization · Advanced Vision and Imaging · Image Enhancement Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
School of Instrument and Electronics, North University of China, Taiyuan 030051, China
Funding
Key research and development project of Shanxi Province · Shanxi Province Basic Research Program · Aviation Science Foundation · Shanxi province key laboratory of quantum sensing and precision measurement · Shanxi Province Graduate Student Innovation Practice Project · Scientific and technological breakthrough of “Light of the Taihu Lake” (basic research)
References (34)
Show source-provided references
1. Temple, S., How, M., Powell, S., Gruev, V., Marshall, N., and Roberts, N. (2021). Thresholds of polarization vision in octopus. J. Exp. Biol., 224.10.1242/jeb.240812 ↗
2. Polarization vision in terrestrial hermit crabs10.1007/s00359-023-01631-z ↗
3. Nugroho, H.A., Cahyadi, A.I., and Ardiyanto, I. (2023). Attitude Control and Low Cost Design of UAV Bicopter. arXiv.
4. Liu, M., Wang, W., Shi, Z., Xie, L., Chen, W., Yan, Y., and Yin, E. (2025). Deep Learning-Based IMU Errors Compensation with Dynamic Receptive Field Mechanism. Advances in Guidance, Navigation and Control, Springer.10.1007/978-981-96-2216-0_10 ↗
5. Flight in GPS-denied environment: Autonomous navigation system for micro-aerial vehicle10.1016/j.ast.2022.107521 ↗
6. Sensor fusion algorithms for orientation tracking via magnetic and inertial measurement units: An experimental comparison survey10.1016/j.inffus.2021.04.009 ↗
7. Adaptive Grid Search Based Pulse Phase and Doppler Frequency Estimation for XNAV10.1109/TAES.2024.3361431 ↗
8. Kendall, A., Grimes, M., and Cipolla, R. (2015, January 7–13). PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization. Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile.10.1109/ICCV.2015.336 ↗
9. A highly robust polarization orientation method based on antisymmetry of skylight polarization pattern10.1016/j.measurement.2022.112070 ↗
10. Li, Z., Li, M., Wu, P., and Li, Y. (2024, January 18–20). Dynamic Obstacle Detection for Quadrotors with Event Cameras. Proceedings of the 2024 4th International Conference on Intelligent Communications and Computing (ICICC), Zhengzhou, China.10.1109/ICICC63565.2024.10780721 ↗
11. Wang, Z., She, H., and Si, W. (2017, January 3–6). Autonomous landing of multi-rotors UAV with monocular gimbaled camera on moving vehicle. Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA), Ohrid, Macedonia.10.1109/ICCA.2017.8003095 ↗
12. Horizon detection in maritime images using scene parsing network10.1049/el.2018.0989 ↗
13. Zardoua, Y., Mohammed, B., Mrabet, M.E., and Abdelali, A. (2021). A Fast Horizon Detector and a New Annotated Dataset for Maritime Video Processing. arXiv.
14. ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM10.1109/TRO.2021.3075644 ↗
15. Accommodating unobservability to control flight attitude with optic flow10.1038/s41586-022-05182-2 ↗
16. UAV attitude estimation based on MARG and optical flow sensors using gated recurrent unit10.1177/15501477211009814 ↗
17. CODNet: A Center and Orientation Detection Network for Power Line Following Navigation
18. Shi, B., Wang, C., Di, Y., Guo, J., Zhang, Z., and Long, Y. (2023). Research on a Horizon Line Detection Method for Unmanned Surface Vehicles in Complex Environments. J. Mar. Sci. Eng., 11.10.3390/jmse11061130 ↗
19. Flores, J., Gonzalez-Hernandez, I., Salazar, S., Lozano, R., and Reyes, C. (2024). Improving Optical Flow Sensor Using a Gimbal for Quadrotor Navigation in GPS-Denied Environment. Sensors, 24.10.3390/s24072183 ↗
20. Aycock, T.M., Lompado, A., and Wheeler, B.M. (2014, January 22–25). Using Atmospheric Polarization Patterns for Azimuth Sensing. Proceedings of the SPIE Defense + Security, Baltimore, MD, USA.10.1117/12.2054107 ↗
21. Gkanias, E., Risse, B., Mangan, M., and Webb, B. (2019). From skylight input to behavioural output: A computational model of the insect polarised light compass. PLoS Comput. Biol., 15.10.1371/journal.pcbi.1007123 ↗
22. Polarized Light Compass-Aided Visual-Inertial Navigation Under Foliage Environment10.1109/JSEN.2017.2725938 ↗
23. A Novel Orientation Method for Polarized Light Compass Under Tilted Conditions10.1109/JSEN.2020.2994104 ↗
24. Comprehensive Heading Error Processing Technique Using Image Denoising and Tilt-Induced Error Compensation for Polarization Compass10.1109/ACCESS.2020.3028418 ↗
25. Attitude-Induced error modeling and compensation with GRU networks for the polarization compass during UAV orientation10.1016/j.measurement.2022.110734 ↗
26. Wu, X., Liu, J., Shen, C., Cao, H., Wang, C., and Tang, J. (2024). Vehicle-Mounted Polarization Orientation Strategy Considering Inclined Pavement and Occlusion Conditions. IEEE Trans. Intell. Veh., 1–12.10.1109/TIV.2024.3385396 ↗
27. Liu, S., Long, W., He, L., Li, Y., and Ding, W. (2021). Retinex-Based Fast Algorithm for Low-Light Image Enhancement. Entropy, 23.10.3390/e23060746 ↗
28. Segmentation-based image defogging using modified dark channel prior10.1186/s13640-020-0493-9 ↗
29. Single Image Haze Removal Using Dark Channel Prior10.1109/TPAMI.2010.168 ↗
30. Kusnandar, T., Santoso, J., and Surendro, K. (2023, June 23). Modification Color Filtering in HSV Color Space. Available online: https://www.researchsquare.com/article/rs-2650337/v1.10.21203/rs.3.rs-2650337/v1 ↗
31. Gaussian-Adaptive Bilateral Filter10.1109/LSP.2020.3024990 ↗
32. A Lane Tracking Method Based on Progressive Probabilistic Hough Transform10.1109/ACCESS.2020.2991930 ↗
33. Bioinspired polarization vision enables underwater geolocalization10.1126/sciadv.aao6841 ↗
34. Evangelista, C., Kraft, P., Dacke, M., Labhart, T., and Srinivasan, M.V. (2014). Honeybee navigation: Critically examining the role of the polarization compass. Philos. Trans. R. Soc. London. Ser. B Biol. Sci., 369.10.1098/rstb.2013.0037 ↗