[论文解读] 3D LiDAR Aided GNSS NLOS Mitigation for Reliable GNSS-RTK Positioning in Urban Canyons

Xikun Liu, Weisong Wen+4 more|arXiv (Cornell University)|Dec 11, 2022

Indoor and Outdoor Localization Technologies被引用 5

一句话总结

本文提出了一种紧密耦合的3D LiDAR辅助GNSS RTK方法，通过从3D点云地图（PCM）中提取的虚拟卫星（VS）观测值，缓解城市峡谷中非视 Line-of-sight（NLOS）和多径误差。通过增强模糊度固定解的可观测性，该方法在复杂城市环境中实现了30%的固定率和分米级定位精度，显著优于传统GNSS-RTK。

ABSTRACT

GNSS and LiDAR odometry are complementary as they provide absolute and relative positioning, respectively. Their integration in a loosely-coupled manner is straightforward but is challenged in urban canyons due to the GNSS signal reflections. Recent proposed 3D LiDAR-aided (3DLA) GNSS methods employ the point cloud map to identify the non-line-of-sight (NLOS) reception of GNSS signals. This facilitates the GNSS receiver to obtain improved urban positioning but not achieve a sub-meter level. GNSS real-time kinematics (RTK) uses carrier phase measurements to obtain decimeter-level positioning. In urban areas, the GNSS RTK is not only challenged by multipath and NLOS-affected measurement but also suffers from signal blockage by the building. The latter will impose a challenge in solving the ambiguity within the carrier phase measurements. In the other words, the model observability of the ambiguity resolution (AR) is greatly decreased. This paper proposes to generate virtual satellite (VS) measurements using the selected LiDAR landmarks from the accumulated 3D point cloud maps (PCM). These LiDAR-PCM-made VS measurements are tightly-coupled with GNSS pseudorange and carrier phase measurements. Thus, the VS measurements can provide complementary constraints, meaning providing low-elevation-angle measurements in the across-street directions. The implementation is done using factor graph optimization to solve an accurate float solution of the ambiguity before it is fed into LAMBDA. The effectiveness of the proposed method has been validated by the evaluation conducted on our recently open-sourced challenging dataset, UrbanNav. The result shows the fix rate of the proposed 3DLA GNSS RTK is about 30% while the conventional GNSS-RTK only achieves about 14%. In addition, the proposed method achieves sub-meter positioning accuracy in most of the data collected in challenging urban areas.

研究动机与目标

• 为解决在城市峡谷中因信号遮挡和多径效应导致GNSS-RTK模糊度固定率低下的问题。
• 通过引入来自LiDAR点云地图的虚拟卫星（VS）观测值，提升模糊度固定解的模型可观测性。
• 在传统方法失效的密集城市环境中，实现可靠、分米级精度的GNSS-RTK定位。
• 在因子图优化框架中，将LiDAR衍生的约束与GNSS伪距和载波相位观测值进行紧密耦合。

提出的方法

• 利用累积的3D点云地图（PCM）中选定的LiDAR特征点生成虚拟卫星（VS）观测值。
• 在因子图优化框架中，将LiDAR衍生的VS观测值与GNSS伪距和载波相位观测值紧密耦合。
• 利用优化后的因子图计算模糊度的精确浮点解，随后应用LAMBDA算法进行整数模糊度固定。
• 利用VS观测值在横向街道方向提供低仰角的几何约束，提升可观测性。
• 采用松耦合的GNSS与LiDAR里程计框架作为基线，但通过引入基于LiDAR-PCM的虚拟卫星实现紧密集成。
• 在公开的UrbanNav数据集上验证该方法，该数据集捕捉了具有挑战性的城市峡谷场景。

实验结果

研究问题

• RQ1 能否通过3D LiDAR点云地图生成的虚拟卫星观测值，提升GNSS-RTK中模糊度固定解的可观测性？
• RQ2 LiDAR辅助的虚拟卫星观测值在多大程度上可缓解城市峡谷中的NLOS和多径误差？
• RQ3 所提出的紧密耦合3DLA GNSS-RTK方法与传统GNSS-RTK相比，在模糊度固定率和定位精度方面表现如何？
• RQ4 LiDAR-PCM数据的集成是否能提升GNSS-RTK在信号遮挡严重城市环境中的性能？

主要发现

• 所提出的3DLA GNSS-RTK在相同UrbanNav数据集上实现了30%的模糊度固定率，而传统GNSS-RTK仅为14%。
• 该方法在大多数复杂城市峡谷环境中均能实现可靠的分米级定位精度。
• 虚拟卫星观测值有效提供了互补的几何约束，尤其在低仰角方向，显著增强了模型的可观测性。
• 因子图优化成功计算出高精度的模糊度浮点解，这对高精度整数模糊度固定至关重要。
• LiDAR-PCM数据的集成显著提升了GNSS-RTK在多径效应强且信号遮挡严重的城市区域中的鲁棒性。