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A LiDAR–INS-aided geometry-based cycle slip resolution for intelligent vehicle in urban environment with long-term satellite signal loss

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Abstract

Intelligent vehicles usually equip with GNSS receivers and MEMS-IMU for localization and light detection and ranging (LiDAR) sensors for perception. Cycle slip detection and repair is significant for the GNSS receivers to achieve high-precision positioning results. We propose an improved geometry-based cycle slip detection and repair method considering the positioning error at the immediate prior epoch and the influence of the satellite geometry change. Experimental results show that our improved method can improve fixed rates of ambiguity resolution compared to the traditional geometry-based method, especially for long-term satellite signal loss. Based on the improved method, we further propose a LiDAR–INS aiding LAMBDA method for cycle slip detection and repair. The INS model and LiDAR scan-to-map matching results are fused by extended Kalman filter (EKF) to calculate between-epoch relative position, which provides a constraint for LAMBDA. Experimental results prove that our LiDAR–INS positioning method can get centimeter-level accuracy for small observation gaps (e.g., 10 s) and decimeter-level accuracy for large observation gaps (e.g., 1 min), which can help achieve high fixed rates and success rates (e.g., 0.85) for large observation gaps (e.g., 200 s) in the urban occlusion environment where prior epoch owns meter-level positioning accuracy.

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Acknowledgements

This research gets support from the National Key R&D Program of China (Grant No. 2023YFB3907100).

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Authors and Affiliations

  1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China

    Hongjuan Zhang, Wenzhuo Li & Bijun Li

  2. Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application, Ministry of Education of China, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China

    Hongjuan Zhang & Bijun Li

  3. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan, 430063, China

    Chuang Qian

  4. GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China

    Hui Liu

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  1. Hongjuan Zhang
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  2. Chuang Qian
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  3. Wenzhuo Li
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  4. Bijun Li
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  5. Hui Liu
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Contributions

HZ, CQ, WL and BL contributed to the conception of the study. HZ and CQ and WL collected, analyzed the data and verified the results. HZ wrote the main manuscript text. BL and HL provided funding. All authors reviewed the manuscript.

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Correspondence to Chuang Qian.

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Zhang, H., Qian, C., Li, W. et al. A LiDAR–INS-aided geometry-based cycle slip resolution for intelligent vehicle in urban environment with long-term satellite signal loss. GPS Solut 28, 61 (2024). https://doi.org/10.1007/s10291-023-01597-0

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