Advancements in Key Parameters of Frequency-Modulated Continuous-Wave Light Detection and Ranging: A Research Review
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Published:2024-09-03
Issue:17
Volume:14
Page:7810
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Wu Zibo12, Song Yue12, Liu Jishun12, Chen Yongyi123, Sha Hongbo12, Shi Mengjie12, Zhang Hao12, Qin Li12, Liang Lei12ORCID, Jia Peng12, Qiu Cheng12, Lei Yuxin12ORCID, Wang Yubing12, Ning Yongqiang12, Zhang Jinlong12, Wang Lijun12
Affiliation:
1. Key Laboratory of Luminescence Science and Technology, Chinese Academy of Sciences & State Key Laboratory of Luminescence Science and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China 2. University of Chinese Academy of Sciences, Beijing 100049, China 3. Jlight Semiconductor Technology Co., Ltd., Changchun 130033, China
Abstract
As LiDAR technology progressively advances, the capability of radar in detecting targets has become increasingly vital across diverse domains, including industrial, military, and automotive sectors. Frequency-modulated continuous-wave (FMCW) LiDAR in particular has garnered substantial interest due to its efficient direct velocity measurement and excellent anti-interference characteristics. It is widely recognized for its significant potential within radar technology. This study begins by elucidating the operational mechanism of FMCW LiDAR and delves into its basic principles. It discuss, in depth, the influence of various parameters on FMCW LiDAR’s performance and reviews the latest progress in the field. This paper proposes that future studies should focus on the synergistic optimization of key parameters to promote the miniaturization, weight reduction, cost-effectiveness, and longevity of FMCW LiDAR systems. This approach aims at the comprehensive development of FMCW LiDAR, striving for significant improvements in system performance. By optimizing these key parameters, the goal is to promote FMCW LiDAR technology, ensuring more reliable and accurate applications in automated driving and environmental sensing.
Funder
Science and Technology Development Project of Jilin Province Outstanding Scientific and Technological Talents Project of Jilin Province Strategic Research and Consulting Project of the Chinese Academy of Engineering National Key Research and Development Program of China Changchun Distinguished Young Scholars Program National Natural Science Foundation of China Dawn Talent Training Program of CIOMP
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