A Survey of mmWave-based Human Sensing: Technology, Platform and Applications

Abstract

With the rapid development of the Internet of Things (IoT) and the rise of 5G communication networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts impacting our life and workspace. mmWave sensing can sense humans and objects in a contactless way, providing fine-grained sensing ability. In the past few years, many mmWave sensing techniques have been proposed and applied in various human sensing applications (e.g., human localization, gesture recognition, and vital monitoring). We discover the need of a comprehensive survey to summarize the technology, platforms and applications of mmWave-based human sensing. In this survey, we first present the mmWave hardware platforms and some key techniques of mmWave sensing. We then provide a comprehensive review of existing mmWave-based human sensing works. Specifically, we divide existing works into four categories according to the sensing granularity: human tracking and localization, motion recognition, biometric measurement and human imaging. Finally, we discuss the potential research challenges and present future directions in this area.

arXiv comment30 pages, 17 figures, IEEE Survey & Tutorial

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Cited by in corpus (5)

• Radio2Text: Streaming Speech Recognition Using mmWave Radio Signals
• A Rydberg atom based system for benchmarking mmWave automotive radar chips
• ProbRadarM3F: mmWave Radar based Human Skeletal Pose Estimation with Probability Map Guided Multi-Format Feature Fusion
• Securing Contrastive mmWave-based Human Activity Recognition against Adversarial Label Flipping
• Meta-Learning-Based People Counting and Localization Models Employing CSI from Commodity WiFi NICs