Instantaneous ego-motion estimation using multiple Doppler radars
Instantaneous ego-motion estimation using multiple Doppler radars
复制标题
使用多个多普勒雷达进行瞬时自我运动估计
DOI：
10.1109/icra.2014.6907064
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
K. Dietmayer
中科院分区：
文献类型：
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作者：
Dominik Kellner;M. Barjenbruch;J. Klappstein;J. Dickmann;K. Dietmayer
自主车辆的运动估计是先进的驾驶辅助系统和移动机器人定位的关键技术。本文提出了一种利用雷达传感器来实时确定自行车组的完整二维运动状态(纵向、横向速度和偏航速度)的稳健算法。它评估至少两个多普勒雷达传感器与其接收到的固定反射(目标)之间的相对运动。基于它们的径向速度在方位角上的分布，剔除了非平稳目标和杂波。估计了自我运动及其对应的协方差矩阵。该算法不需要聚类或杂波抑制等任何预处理步骤，也不包含任何模型假设。传感器可以安装在车辆上的任何位置。不需要公共视场，避免了空间中的目标关联。作为一个额外的好处，所有目标都会立即被标记为静止或非静止。
The estimation of the ego-vehicle's motion is a key capability for advanced driving assistant systems and mobile robot localization. The following paper presents a robust algorithm using radar sensors to instantly determine the complete 2D motion state of the ego-vehicle (longitudinal, lateral velocity and yaw rate). It evaluates the relative motion between at least two Doppler radar sensors and their received stationary reflections (targets). Based on the distribution of their radial velocities across the azimuth angle, non-stationary targets and clutter are excluded. The ego-motion and its corresponding covariance matrix are estimated. The algorithm does not require any preprocessing steps such as clustering or clutter suppression and does not contain any model assumptions. The sensors can be mounted at any position on the vehicle. A common field of view is not required, avoiding target association in space. As an additional benefit, all targets are instantly labeled as stationary or non-stationary.