在大气雨条件下使用自动驾驶汽车的光子雷达进行多重目标检测
Sushank Chaudhary1, Sunita Khichar2, Yahui Meng3
1School of Computer, Guangdong University of Petrochemical Technology, Maoming, China.
PloS one
|May 13, 2025
概括
这项研究评估了光子雷达在大气动荡和雨下的性能,这对自动驾驶汽车至关重要. 暴雨和流严重降低信号检测,特别是在更远的距离.
科学领域:
- 光学和光子学 在光学和光子学.
- 雷达系统工程 雷达系统工程
- 环境传感器环境传感器
背景情况:
- 光子雷达为自动驾驶汽车提供高精度传感.
- 诸如大气动荡和雨等环境因素会降低雷达的性能.
- 准确的障碍物检测对于自动驾驶汽车的安全至关重要.
研究的目的:
- 在各种环境条件下评估光子雷达系统的性能.
- 分析Gamma-Gamma大气动荡和降雨减弱对目标检测的影响.
- 为了评估不同距离的多个目标的性能.
主要方法:
- 模拟在自由空间中的光子雷达性能,玛玛流和轻微/大雨.
- 由于大气流导致的信号变化的建模.
- 量化因降雨减弱而导致的收到功率减少.
主要成果:
- 马-马流会导致信号波动,随着距离的增加而增加.
- 暴雨导致显著的功率损失 (在100米处高达1.5dBm).
- 雨和流效应的结合将收到的功率降低到-100.4dBm在大雨下150米处.
结论:
- 环境条件对光子雷达性能产生重大影响,需要考虑设计.
- 需要适应性雷达技术来减轻不利的天气影响.
- 该研究展示了光子雷达在自动驾驶汽车中的潜力,其优化了多目标检测策略.
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