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arXiv 提交日期: 2026-06-22
📄 Abstract - Scene-agnostic ALS boresight self-calibration

ALS boresight calibration has relied for two decades on dedicated flight patterns over structured scenes containing planar surfaces of varied aspect and slope. While reliable, this approach imposes constraints on the scene content and operations, which limits its applicability to boresight recovery within routine mapping missions. We present a practical approach that substantially relaxes these requirements by replacing plane-based constraints with scene-agnostic point-to-point correspondences extracted automatically from overlapping ALS strips. Two complementary formulations are proposed to estimate boresight with laser vector observations: (i) a simpler parametric adjustment utilizing INS/GNSS trajectory; (ii) a rigorous formulation treating GNSS and raw inertial data within an existing factor-graph, i.e. a dynamic network, where boresight is added as an additional parameter. Both formulations are evaluated across four operational ALS flights equipped with five inertial systems, covering a wide range of flight altitudes, overlap geometries, terrain types and inertial sensor classes. The analysis draws a clear boundary between the legacy plane-based conditioning that falls short outside the calibration scenario and the proposed formulations, which either recover or absorb boresight effects under conventional mapping geometry. Among them, the lightweight formulation is sufficient for boresight recovery using tactical and navigation grade inertial sensors, while the general factor-graph approach is clearly superior when the inertial sensor errors are less observable within an optimal smoother. This supports the hypothesis that, for INS/GNSS trajectory of sufficient quality, the boresight calibration can be performed without particular scene prerequisites during routine mapping operations using a minimum of 3-4 overlapping strips, with either proposed formulation...

顶级标签: systems machine learning
详细标签: boresight calibration als self-calibration point-to-point correspondence factor-graph 或 搜索:

与场景无关的ALS视轴自校准方法 / Scene-agnostic ALS boresight self-calibration


1️⃣ 一句话总结

本文提出了一种无需依赖特定场景结构(如平面)的激光雷达扫描仪视轴自校准方法,通过自动提取重叠条带间的点云对应关系,结合惯导/卫星定位数据,实现了在常规测绘任务中仅需3-4个重叠条带即可完成高精度校准,显著降低了传统校准对飞行模式和场景设计的严格要求。

源自 arXiv: 2606.23101