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基于毫米波雷达的传感,其应用及其机器学习技术的最新进展:一篇评论
A Soumya1, C Krishna Mohan1, Linga Reddy Cenkeramaddi2
1Department of Computer Science Engineering, Indian Institute of Technology, Hyderabad 502285, India.
Sensors (Basel, Switzerland)
|November 14, 2023
概括
毫米波 (mmWave) 雷达传感器在各种条件下提供强大的性能,从而实现先进的应用. 本综述探讨了毫米波雷达传感,应用和机器学习集成的实际发展.
科学领域:
- 电磁学和传感器技术
- 机器学习和人工智能的人工智能
- 数据科学和信号处理数据科学和信号处理
背景情况:
- 毫米波 (mmWave) 雷达传感器已经取得了显著的进步,比其他传感技术提供了独特的优势.
- 关键的好处包括在各种照明条件下 (明亮,耀眼,无光) 的可靠运行以及优越的天线小型化和范围分辨率.
- 数据集的日益可用性推动了毫米波雷达数据的集成到机器学习 (ML) 中,用于各种应用.
研究的目的:
- 为提供基于毫米波雷达的传感提供了全面的审查.
- 详细介绍关键性能指标,各种应用程序和相关的机器学习技术.
- 作为使用毫米波雷达和ML的开发人员的实际参考.
主要方法:
- 对毫米波雷达工作频段,类型和关键规格的审查.
- 分析毫米波雷达数据解释方法的分析.
- 对各种任务的毫米波雷达数据应用的机器学习算法的探索.
主要成果:
- 毫米波雷达技术可以实现诸如手势检测,避障和汽车驾驶等关键应用.
- 该评论对毫米波雷达传感的广泛应用领域进行了分类和讨论.
- 确定并总结了各种适用于毫米波雷达数据处理的机器学习技术.
结论:
- 毫米波雷达传感器是多功能和强大的工具,在许多领域都有广泛的应用.
- 毫米波雷达数据和机器学习之间的协同作用显著提高了传感能力.
- 本综述提供了利用毫米波雷达技术与机器学习的基础指南.


