基于分布式单通道雷达传感器的自我运动估计

Maximilian Steiner, Omar Hammouda, C. Waldschmidt
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引用次数: 17

摘要

汽车的运动对所有环境传感器的相对测量结果有很大的影响。因此,对配备传感器的汽车的自我运动的精确了解对于更高级别的信号处理(如映射或目标参数的估计)非常重要。这可以通过多个简单的雷达传感器实现一次测量。多个传感器对同一视场进行距离和速度测量,对静止目标进行联合处理和滤波。该数据集用于确定车辆在x和y平面上的速度和偏航率。该方法的一个优点是传感器简单,不需要在方位面上进行角度估计,同时仍能提供可比较的结果。此外,这种方法适用于最少数量的两个传感器。
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Ego-Motion Estimation using Distributed Single-Channel Radar Sensors
The motion of a car has a vast impact on the relative measurements of all environmental sensors. Consequently, the precise knowledge of the ego-motion of a sensor equipped car is important for higher level signal processing like mapping or the estimation of the target parameters. This can be achieved by multiple simple radar sensors with a single measurement. The range and the velocity measurements conducted by multiple sensors that are observing a common field of view are jointly processed and filtered for stationary targets. This dataset is used to determine the velocity and the yaw rate of the vehicle in the x- and y-plane. An advantage of the proposed approach is the simplicity of the sensors which do not need the capability of angle estimation in the azimuth plane, while still providing comparable results. In addition, this approach works with a minimum number of two sensors.
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