适用汽车智能驾驶的多光谱激光雷达波长选择可行性研究
投稿时间:2019-08-22  修订日期:2019-11-21  点此下载全文
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作者单位E-mail
宋绍京 上海第二工业大学 通信与信息工程系上海 201209 sjsong@sspu.edu.cn 
陈育伟 Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, 02431 Masala, Finland  
胡海江 上海第二工业大学 通信与信息工程系上海 201209  
胡金艳 上海第二工业大学 通信与信息工程系上海 201209  
龚玉梅 上海第二工业大学 通信与信息工程系上海 201209  
邵慧 Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, National Land Survey of Finland, 02431 Masala, Finland
安徽建筑大学 电子与信息工程学院合肥 230601 
 
中文摘要:在汽车智能驾驶系统中,激光雷达由于其独特的三维成像能力,成为场景探测感知传感器群组中不可或缺的组成部分。为提升单一波长激光雷达在物性探测分类和状态上的性能,借鉴多光谱探测具有物性探测能力的原理,论文对适用于汽车智能驾驶的多光谱激光雷达的波段选择进行了可行性研究,利用主成分分析法对智能驾驶中典型目标进行光谱计算及分析,结合激光光源特性以及光电探测器的特性,综合多光谱激光雷达波段选择方法和智能驾驶应用场景中典型目标地物光谱特性分析,以及商用激光雷达的可获得性, 得出了适用汽车智能驾驶的多光谱激光雷达的波长可以选择808nm,905nm,1064nm,1310nm,并通过测试验证了多光谱激光雷达所选波长的有效性。
中文关键词:场景感知  主成分分析  智能驾驶  激光雷达  波长选择
 
The Feasibility Study of Wavelength Selection of Multispectral Lidarfor Autonomous Driving
Abstract:In the autonomous driving system of automobile, in order to improve the performance of single-wavelength Lidar in physical property detection classification and state, and draw lessons from the principle that multi-spectral detection has physical property detection ability, this paper studies the band selection of multi-spectral Lidar, calculates and analyses the spectrum of typical targets in autonomous driving by using principal component analysis method, and combines the characteristics of laser source and photoelectric detection. The characteristics of the detector, the band selection method of multispectral Lidar and the spectral characteristics analysis of typical targets in autonomous driving application scenarios are synthesized. The central wavelength of the multispectral Lidar suitable for autonomous driving of automobiles is 808 nm, 905 nm, 1064 nm and 1310 nm. The validity of the selected wavelength of the multispectral Lidar is verified by testing.
keywords:band selection  principal component analysis  autonomous driving  Lidar
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