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首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >Tracking of Extended Objects with High-Resolution Doppler Radar
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Tracking of Extended Objects with High-Resolution Doppler Radar

机译：高分辨率多普勒雷达跟踪扩展对象

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摘要

In an urban environment, one of the key challenges remains to be the reliable estimation of the other traffic participants' motion state. Due to the highly nonlinear motions in city traffic, an instant and precise estimation of heading direction, velocity, and, particularly, yaw rate is required. Radar sensors are well suited for this task due to their robustness to environmental influences and direct measurement of the radial (Doppler) velocity. High-resolution radars receive multiple reflections from an extended object. In comparison to state-of-the-art approaches, not only is the Doppler velocity of a single reference point taken into account, but also is the distribution of the Doppler velocity across the vehicle analyzed. The velocity profile is derived with characteristic features and a corresponding sample covariance. These are fused into an unscented Kalman filter, resulting in a significant accuracy improvement and a reduction in the latency of the filter to almost zero during a change in motion or initialization. This yields a great improvement in determining the trajectories of potential critical objects, increasing the time to avoid collisions. Furthermore, the approach enables simultaneous identification of the rotation center of the object, which is essential for the tracking of highly dynamic maneuvers. All approaches were implemented and evaluated on a large experimental data set using highly precise reference systems as ground truth. The results show an impressive improvement in the accuracy of the yaw rate estimation of a factor of 3–4 compared with state-of-the-art approaches in a dynamic scenario.
机译：在城市环境中，关键挑战之一仍然是对其他交通参与者的运动状态的可靠估计。由于城市交通中的高度非线性运动，因此需要对行进方向，速度，尤其是偏航率进行即时而精确的估计。雷达传感器因其对环境影响的鲁棒性和径向（多普勒）速度的直接测量而非常适合于此任务。高分辨率雷达接收来自扩展对象的多次反射。与最新方法相比，不仅要考虑单个参考点的多普勒速度，而且还要分析整个车辆上的多普勒速度分布。速度分布图具有特征和相应的样本协方差。这些被融合到一个无味的卡尔曼滤波器中，从而在运动或初始化发生变化时显着提高了精度，并将滤波器的等待时间减少到几乎为零。这在确定潜在关键物体的轨迹方面产生了很大的改进，从而增加了避免碰撞的时间。此外，该方法能够同时识别物体的旋转中心，这对于跟踪高动态操纵至关重要。所有方法均使用高精度参考系统作为基础，在大型实验数据集上实施和评估。结果表明，与动态方案中的最新方法相比，偏航率估算的准确性有了令人印象深刻的3-4倍的改善。

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