论文标题
Tex-Cup：德克萨斯大学城市定位挑战赛
TEX-CUP: The University of Texas Challenge for Urban Positioning
论文作者
论文摘要
引入了在德克萨斯州奥斯汀市密集的城市中心收集的公共基准数据集，以评估基于GNSS的多传感器的城市定位。现有的有关本地化和/或探射评估的公共数据集基于LIDAR，相机和雷达等传感器。 GNS在这些数据集中的作用通常仅限于与高端惯性导航系统（INS）结合使用的参考轨迹的生成。相比之下，本文介绍的数据集提供了宽带中间频率（IF）GNSS数据的原始ADC输出，以及来自惯性测量单元（IMU）和立体相机单元的紧密同步的原始测量。该数据集将启用从信号跟踪到状态估计的完整GNSS堆栈以及传感器与其他汽车传感器的融合。该数据集可从http://radionavlab.ae.utexas.edu获得公共数据集下方。从世界各地许多密集的城市中心收集和共享类似数据集的努力正在进行中。
A public benchmark dataset collected in the dense urban center of the city of Austin, TX is introduced for evaluation of multi-sensor GNSS-based urban positioning. Existing public datasets on localization and/or odometry evaluation are based on sensors such as lidar, cameras, and radar. The role of GNSS in these datasets is typically limited to the generation of a reference trajectory in conjunction with a high-end inertial navigation system (INS). In contrast, the dataset introduced in this paper provides raw ADC output of wideband intermediate frequency (IF) GNSS data along with tightly synchronized raw measurements from inertial measurement units (IMUs) and a stereoscopic camera unit. This dataset will enable optimization of the full GNSS stack from signal tracking to state estimation, as well as sensor fusion with other automotive sensors. The dataset is available at http://radionavlab.ae.utexas.edu under Public Datasets. Efforts to collect and share similar datasets from a number of dense urban centers around the world are under way.
