论文标题
全天低下50厘米雷达惯性定位
All-Weather sub-50-cm Radar-Inertial Positioning
论文作者
论文摘要
超出阳光和干燥的气体范围之外的自动地面车辆的部署将需要基于无线电波而不是近乎可见光的轻射辐射来下车道级别的定位技术。像人类的视线一样，在低可见性条件下，LiDAR和相机的表现也很差。本文开发并展示了一种基于全天候传感器的可靠50 cm精确的城市地面车辆定位的新技术。该技术结合了一项计算效率的全球雷达扫描批次批次批准算法中的较大估计管道，该管道将融合来自商业上可用的低成本汽车雷达，低成本惯性传感器，车辆运动约束，并在可用时进行精确的GNS测量。在广泛而现实的城市数据集上评估绩效。与地面真相的比较表明，在德克萨斯州奥斯汀市城市中心的60分钟内，该技术在水平位置保持低于50 cm的5级误差，标题为0.5度。
Deployment of automated ground vehicles beyond the confines of sunny and dry climes will require sub-lane-level positioning techniques based on radio waves rather than near-visible-light radiation. Like human sight, lidar and cameras perform poorly in low-visibility conditions. This paper develops and demonstrates a novel technique for robust sub-50-cm-accurate urban ground vehicle positioning based on all-weather sensors. The technique incorporates a computationally-efficient globally-optimal radar scan batch registration algorithm into a larger estimation pipeline that fuses data from commercially-available low-cost automotive radars, low-cost inertial sensors, vehicle motion constraints, and, when available, precise GNSS measurements. Performance is evaluated on an extensive and realistic urban data set. Comparison against ground truth shows that during 60 minutes of GNSS-denied driving in the urban center of Austin, TX, the technique maintains 95th-percentile errors below 50 cm in horizontal position and 0.5 degrees in heading.
