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Volume 26
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10.3390/s26030800
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

GPIS-Based Calibration for Non-Overlapping Dual-LiDAR Systems Using a 2.5D Calibration Framework

by
Huan Yu
1,
Xiaohong Zhang
2,3,*,
Ming Li
4,
Desheng Zhuo
1,
Pin Zhang
5,
Man Li
6 and
Yuanyuan Shi
6
1
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
2
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
3
Hubei Luojia Laboratory, Wuhan 430079, China
4
School of Artificial Intelligence, Wuhan University, Wuhan 430072, China
5
School of Computer Science, Wuhan University, Wuhan 430079, China
6
Dongfeng Motor Corporation Technical Center, Wuhan 430010, China
*
Author to whom correspondence should be addressed.
Sensors 2026, 26(3), 800; https://doi.org/10.3390/s26030800 (registering DOI)
Submission received: 1 December 2025 / Revised: 21 January 2026 / Accepted: 22 January 2026 / Published: 25 January 2026
(This article belongs to the Section Radar Sensors)
Versions Notes

Abstract

Dual-LiDAR systems are widely deployed in autonomous driving, yet extrinsic calibration remains challenging in non-overlapping field-of-view (FoV) configurations where correspondence-based methods are unreliable. We propose an engineering-oriented 2.5D calibration framework that estimates horizontal extrinsics (x,y,yaw) via motion-guided planar alignment and then refines them using Gaussian Process Implicit Surfaces (GPIS), which provide continuous and probabilistic surface constraints from spatially disjoint scans. This design avoids calibration targets and reduces dependence on strong scene assumptions, improving robustness under noise and weak structure. Extensive high-fidelity simulation experiments demonstrate centimeter-level lateral accuracy and sub-degree yaw error, consistently outperforming representative motion-based and BEV-based baselines under both clean and noisy settings. To further assess real-world applicability, we conduct a preliminary nuScenes case study by splitting LiDAR scans into front and rear subsets to emulate a non-overlapping dual-LiDAR setup, achieving improved yaw accuracy and competitive lateral precision. Overall, the proposed method serves as a practical refinement stage for non-overlapping dual-LiDAR calibration, with a favorable balance of accuracy, robustness, and engineering feasibility.
Keywords: dual-LiDAR systems; extrinsic calibration; GPIS; surface modeling; non-overlapping field of view; autonomous driving dual-LiDAR systems; extrinsic calibration; GPIS; surface modeling; non-overlapping field of view; autonomous driving

Share and Cite

MDPI and ACS Style

Yu, H.; Zhang, X.; Li, M.; Zhuo, D.; Zhang, P.; Li, M.; Shi, Y. GPIS-Based Calibration for Non-Overlapping Dual-LiDAR Systems Using a 2.5D Calibration Framework. Sensors 2026, 26, 800. https://doi.org/10.3390/s26030800

AMA Style

Yu H, Zhang X, Li M, Zhuo D, Zhang P, Li M, Shi Y. GPIS-Based Calibration for Non-Overlapping Dual-LiDAR Systems Using a 2.5D Calibration Framework. Sensors. 2026; 26(3):800. https://doi.org/10.3390/s26030800

Chicago/Turabian Style

Yu, Huan, Xiaohong Zhang, Ming Li, Desheng Zhuo, Pin Zhang, Man Li, and Yuanyuan Shi. 2026. "GPIS-Based Calibration for Non-Overlapping Dual-LiDAR Systems Using a 2.5D Calibration Framework" Sensors 26, no. 3: 800. https://doi.org/10.3390/s26030800

APA Style

Yu, H., Zhang, X., Li, M., Zhuo, D., Zhang, P., Li, M., & Shi, Y. (2026). GPIS-Based Calibration for Non-Overlapping Dual-LiDAR Systems Using a 2.5D Calibration Framework. Sensors, 26(3), 800. https://doi.org/10.3390/s26030800

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