This paper presents an approach to radar odometry on $SE(3)$ which utilizes a constant acceleration motion prior. The motion prior is integrated into a sliding window optimization scheme. We use the Magnus expansion to accurately integrate the motion prior while maintaining real-time performance. In addition, we adopt a polar measurement model to better represent radar detection uncertainties. Our estimator is evaluated using a large real-world dataset from a prototype high-resolution radar sensor. The new motion prior and measurement model signifcantly improve odometry performance relative to the constant velocity motion prior and Cartesian measurement model from our previous work, particularly in roll, pitch and height.
翻译:本文介绍了对$SE(3)美元进行雷达观测的方法,该方法先使用恒定加速运动,先并入滑动窗口优化计划。我们使用 Magnus 扩展来精确整合先前的运动,同时保持实时性能。此外,我们采用了极度测量模型,以更好地代表雷达探测的不确定性。我们的测算器使用原型高分辨率雷达传感器的大型真实世界数据集进行评估。新的先动和测量模型标志性地改进了相对于我们先前工作,特别是滚动、投放和高度的恒定速度运动和笛卡尔测量模型的奥氏测量性能。