针对极地地形的雷达里程计，提出新方法提升动态倾斜下的定位精度。
Radar Odometry Subject to High Tilt Dynamics of Subarctic Environments
- 基于倾斜邻近子地图搜索与垂直位移硬阈值，融合雷达与惯性数据
- 在2公里动态轨迹上优于第二名0.3%，极端倾斜下误差显著降低
- 适合高动态极地或崎岖地形的自动驾驶系统研发人员
旋转式FMCW雷达里程计通常假设地面平坦，但在极地等动态地形中，这种假设失效。本文在存在高达13°俯仰差和4°滚转差的严苛条件下，评估了三种现有雷达里程计方法，其绝对俯仰和滚转分别可达30°和8°。为此，提出一种新型雷达-惯性里程计方法，采用倾斜邻近子地图搜索及点云与旋转轴间垂直位移的硬阈值策略。实验表明，该方法在城市基准测试中表现领先，在长达2公里的动态轨迹上相较次优方法提升0.3%。最后，针对具有高侧滑和陡坡穿越特征的复杂雷达序列进行分析，验证了方法鲁棒性。
原文摘要 · Abstract (English)
Rotating FMCW radar odometry methods often assume flat ground conditions. While this assumption is sufficient in many scenarios, including urban environments or flat mining setups, the highly dynamic terrain of subarctic environments poses a challenge to standard feature extraction and state estimation techniques. This paper benchmarks three existing radar odometry methods under demanding conditions, exhibiting up to 13° in pitch and 4° in roll difference between consecutive scans, with absolute pitch and roll reaching 30° and 8°, respectively. Furthermore, we propose a novel radar-inertial odometry method utilizing tilt-proximity submap search and a hard threshold for vertical displacement between scan points and the estimated axis of rotation. Experimental results demonstrate a state-of-the-art performance of our method on an urban baseline and a 0.3% improvement over the second-best comparative method on a 2-kilometer-long dynamic trajectory. Finally, we analyze the performance of the four evaluated methods on a complex radar sequence characterized by high lateral slip and a steep ditch traversal.
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