Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
| dc.contributor.advisor | Wen, Weisong (AAE) | en_US |
| dc.contributor.advisor | Hsu, Li-ta (AAE) | en_US |
| dc.creator | Liu, Xikun | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/14383 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | 3D LiDAR aided GNSS-RTK positioning with NLOS correction and consistent fusion for autonomous systems in urban canyons | en_US |
| dcterms.abstract | Global Navigation Satellite System (GNSS) is widely used in intelligent navigation systems. GNSS real-time kinematic (RTK) has shown centimeter-level absolute positioning results in open-sky areas. However, in areas with complex urban canyons such as Hong Kong, the accuracy of GNSS is severely diminished due to signal blockage and reflection. Polluted GNSS measurements as well as poor satellite geometry are two main reasons for deteriorating urban GNSS-RTK positioning performance. Such a problem significantly affects the application of intelligent navigation systems in urban environments. | en_US |
| dcterms.abstract | To address this problem, the complementary roles of the Light Detection and Ranging (LiDAR) sensor and GNSS are explored in existing works. LiDAR, as an active ranging sensor, not only enables precise relative positioning but also allows digital modeling of the surrounding environment. Recently proposed 3D LiDAR-aided (3DLA) GNSS methods employ the point cloud map to identify the non-line-of-sight (NLOS) reception of GNSS signals for further exclusion and remodeling. This facilitates the GNSS receiver to obtain improved urban positioning. However, due to the remained multipath receptions and poor geometry, the positioning error can still reach several meters. On the other side, GNSS and LiDAR odometry are well combined as they provide absolute and relative positioning, respectively. Their integration in a loosely-coupled manner is straightforward but is still challenged due to the GNSS signal pollution and poor geometry. Therefore, utilizing tightly-coupled GNSS/LiDAR integration for improving GNSS geometry needs to be studied. | en_US |
| dcterms.abstract | In this thesis, we explored the 3D LiDAR aided GNSS-RTK positioning method in terms of 3D LiDAR aided GNSS outlier mitigation and tightly-coupled GNSS/LiDAR integration for geometry improvement. We first focused on further improving the reliability of 3D LiDAR-aided NLOS mitigation and improving the efficiency of tightly-coupled LiDAR/GNSS integration. Further, we proposed GLIO, a GNSS/LiDAR/IMU integrated estimator that tightly fuses all raw measurements using two stages of factor graph optimization (FGO) to achieve globally consistent and continuous pose estimation. Specifically, we designed an iterated coarse-to-fine batch integration between GNSS and LiDAR for global NLOS exclusion. Moreover, we proposed an accurate NLOS correction method by Doppler-aided direction-of-arrival (DOA) estimation and 3D LiDAR-aided reflection restoration. Different from the conventional model, or LiDAR-based NLOS correction methods, the proposed method does not rely on the shortest path assumption and therefore is able to correct NLOS receptions with errors exceeding 100 meters. | en_US |
| dcterms.abstract | The effectiveness of the proposed methods in this thesis are extensively evaluated and verified through the challenging dataset involving highly urbanized areas. The proposed system achieves great improvement in positioning accuracy compared with the traditional GNSS positioning method and representative integration with the LiDAR/IMU system. The results also show that the proposed system can achieve real-time positioning capability with higher robustness in a highly urbanized area using commercial-level GNSS receivers and LiDAR/IMU sensor kit. | en_US |
| dcterms.extent | xv, 128 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2026 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
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