Kristof Hofrichter, Clemens Linnhoff, Lukas Elster, Steven Peters
{"title":"FMCW Lidar Simulation with Ray Tracing and Standardized Interfaces","authors":"Kristof Hofrichter, Clemens Linnhoff, Lukas Elster, Steven Peters","doi":"10.4271/2024-01-2977","DOIUrl":null,"url":null,"abstract":"In pursuit of safety validation of automated driving functions, efforts are being made to accompany real world test drives by test drives in virtual environments. To be able to transfer highly automated driving functions into a simulation, models of the vehicle’s perception sensors such as lidar, radar and camera are required. In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. This is due to advanced capabilities such as directly measuring the target’s relative radial velocity based on the Doppler effect. In this work, an FMCW lidar sensor simulation model is introduced, which is divided into the components of signal propagation and signal processing. The signal propagation is modeled by a ray tracing approach simulating the interaction of light waves with the environment. For this purpose, an ASAM Open Simulation Interface (OSI) object list referencing virtual 3D objects provides the input for the ray tracer. The divergence of the continuous laser beam is approximated by super-sampling the beam with multiple rays, the calculation of the received power is supported by the future ASAM OpenMATERIAL standard. Subsequently, the output of the ray tracer serves as the input of the signal processing that adapts the so-called Fourier tracing from the field of radar sensor simulation. This approach uses the range and velocity information of the individual rays to estimate the frequency spectrum of the intermediate frequency signal. A subsequent peak detection algorithm determines the output of the model, which is provided in the form of OSI lidar detections. Verification scenarios are tested to check the plausibility of the output and the source code of the signal processing is made available as open source.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAE Technical Paper Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4271/2024-01-2977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In pursuit of safety validation of automated driving functions, efforts are being made to accompany real world test drives by test drives in virtual environments. To be able to transfer highly automated driving functions into a simulation, models of the vehicle’s perception sensors such as lidar, radar and camera are required. In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. This is due to advanced capabilities such as directly measuring the target’s relative radial velocity based on the Doppler effect. In this work, an FMCW lidar sensor simulation model is introduced, which is divided into the components of signal propagation and signal processing. The signal propagation is modeled by a ray tracing approach simulating the interaction of light waves with the environment. For this purpose, an ASAM Open Simulation Interface (OSI) object list referencing virtual 3D objects provides the input for the ray tracer. The divergence of the continuous laser beam is approximated by super-sampling the beam with multiple rays, the calculation of the received power is supported by the future ASAM OpenMATERIAL standard. Subsequently, the output of the ray tracer serves as the input of the signal processing that adapts the so-called Fourier tracing from the field of radar sensor simulation. This approach uses the range and velocity information of the individual rays to estimate the frequency spectrum of the intermediate frequency signal. A subsequent peak detection algorithm determines the output of the model, which is provided in the form of OSI lidar detections. Verification scenarios are tested to check the plausibility of the output and the source code of the signal processing is made available as open source.
为了对自动驾驶功能进行安全验证,人们正在努力通过虚拟环境中的试驾来配合真实世界中的试驾。为了能够将高度自动驾驶功能转移到模拟中,需要建立激光雷达、雷达和摄像头等车辆感知传感器的模型。除了传统的脉冲飞行时间(ToF)激光雷达外,商用频率调制连续波(FMCW)激光雷达的日益普及也激发了人们对环境感知领域的兴趣。这是由于激光雷达具有基于多普勒效应直接测量目标相对径向速度等先进功能。本研究介绍了一种 FMCW 激光雷达传感器仿真模型,该模型分为信号传播和信号处理两个部分。信号传播模型采用光线跟踪方法,模拟光波与环境的相互作用。为此,ASAM 开放式仿真接口(OSI)对象列表引用了虚拟三维对象,为光线追踪器提供了输入。连续激光光束的发散是通过多条射线对光束进行超采样近似得到的,接收功率的计算由未来的 ASAM OpenMATERIAL 标准支持。随后,射线追踪器的输出作为信号处理的输入,该信号处理采用雷达传感器模拟领域的所谓傅立叶追踪法。这种方法利用单条射线的射程和速度信息来估算中频信号的频谱。随后的峰值检测算法决定了模型的输出,输出以 OSI 激光雷达检测的形式提供。对验证方案进行了测试,以检查输出的合理性,信号处理的源代码以开放源代码的形式提供。