arXiv:2512.05932cs.ROcs.CV2025-12被引 2

高精度模拟车载激光雷达,包含光晕与环境光影响。

Physically-Based Simulation of Automotive LiDAR

  • 基于物理渲染的近红外建模,支持单次反射与回光脉宽。
  • 通过实验室测量确定光束扩散、接收灵敏度等参数,精度达0.01°。
  • 适配不同系统,可用于自动驾驶传感器测试与验证。

我们提出一种用于模拟车载时间飞行(ToF)激光雷达的解析模型,包含光晕效应、回波脉宽及环境光影响,并通过光学实验室测量系统性地确定模型参数。该模型在近红外域采用基于物理的渲染(PBR),假设单次反射和逆向反射,基于着色或光线追踪生成的栅格化图像,包含传感器自身发射光以及来自非相关光源(如阳光)的杂散光。传感器光束与接收二极管灵敏度采用可调光束指向模式与非零直径建模。根据系统特性、计算能力与输出需求,可选择不同(非实时)计算方法。模型参数包括系统特有属性:激光束的物理扩散、接收二极管灵敏度;发射光强度;反射光强度与回波脉宽之间的转换关系;以及场景参数如环境光照、目标位置与表面属性。系统特有参数通过在0.01°分辨率下,利用光度计与转台对不同目标表面的光通量测量获得,为当前最佳分辨率。该方法已成功校准并测试于两款车载激光雷达系统:Valeo Scala Gen. 2 和 Blickfeld Cube 1。两者在性能与接口上差异显著,但关键模型参数均成功提取。

原文摘要 · Abstract (English)

We present an analytic model for simulating automotive time-of-flight (ToF) LiDAR that includes blooming, echo pulse width, and ambient light, along with steps to determine model parameters systematically through optical laboratory measurements. The model uses physically based rendering (PBR) in the near-infrared domain. It assumes single-bounce reflections and retroreflections over rasterized rendered images from shading or ray tracing, including light emitted from the sensor as well as stray light from other, non-correlated sources such as sunlight. Beams from the sensor and sensitivity of the receiving diodes are modeled with flexible beam steering patterns and with non-vanishing diameter. Different (all non-real time) computational approaches can be chosen based on system properties, computing capabilities, and desired output properties. Model parameters include system-specific properties, namely the physical spread of the LiDAR beam, combined with the sensitivity of the receiving diode; the intensity of the emitted light; the conversion between the intensity of reflected light and the echo pulse width; and scenario parameters such as environment lighting, positioning, and surface properties of the target(s) in the relevant infrared domain. System-specific properties of the model are determined from laboratory measurements of the photometric luminance on different target surfaces aligned with a goniometer at 0.01° resolution, which marks the best available resolution for measuring the beam pattern. The approach is calibrated for and tested on two automotive LiDAR systems, the Valeo Scala Gen. 2 and the Blickfeld Cube 1. Both systems differ notably in their properties and available interfaces, but the relevant model parameters could be extracted successfully.

激光雷达仿真建模自动驾驶物理渲染

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