High-precision vehicle positioning is key to the implementation of modern driving systems in urban environments. Global Navigation Satellite System (GNSS) carrier phase measurements can provide millimeter- to centimeter-level positioning, provided that the integer ambiguities are correctly resolved. Abundant code measurements are often used to facilitate integer ambiguity resolution (IAR), however, they suffer from signal blockage and multipath in urban canyons. In this contribution, a lidar-aided instantaneous ambiguity resolution method is proposed. Lidar measurements, in the form of 3D keypoints, are generated by a learning-based point cloud registration method using a pre-built HD map and integrated with GNSS observations in a mixed measurement model to produce precise float solutions, which in turn increase the ambiguity success rate. Closed-form expressions of the ambiguity variance matrix and the associated Ambiguity Dilution of Precision (ADOP) are developed to provide a priori evaluation of such lidar-aided ambiguity resolution performance. Both analytical and experimental results show that the proposed method enables successful instantaneous IAR with limited GNSS satellites and frequencies, leading to centimeter-level vehicle positioning.
翻译:全球导航卫星系统(GNSS)载体阶段测量可提供毫米至厘米水平的定位,前提是整数模糊度得到正确解决; 大量代码测量往往用于促进整数模糊度的解析(IAR),然而,在城市峡谷中,它们受到信号阻隔和多路径的困扰; 在这项贡献中,提议了利达尔辅助的瞬间模糊度解析方法; 利达尔以3D关键点的形式进行的基于学习的点云登记方法生成了3D关键点的测算,采用预先制作的HD地图,并与全球导航卫星系统观测纳入混合测量模型,以产生精确的浮点解决方案,这反过来又增加了模糊度的成功率; 开发了模糊度差异矩阵的封闭式表达方式和与此相关的精度模糊度分解(ADOP),以便对这种里达尔辅助的模糊度解析性性性性表现进行事先评估; 分析和实验结果都表明,拟议的方法能够以有限的全球导航卫星系统卫星和频率成功进行瞬时空的IAR,导致公分位车辆定位。