A Survey of Wireless Sensing Human Posture Recognition Research

With the development of human-computer interaction, virtual reality, and other fields, the importance of human posture estimation technology is becoming increasingly prominent.Traditional optical methods are limited by light, occlusion, and privacy issues, whereas wireless sensing techniques have become a core research direction owing to their non-invasiveness and environmental robustness.In this study, nine cutting-edge wireless sensing technologies based on millimeter-wave radar, through-wall radar, and WiFi signals were analyzed in terms of hardware suitability, signal processing frameworks, and deep learning model optimization strategies.Millimeter-wave radar technology forms a technological divide between accuracy, light weight, and multi-person robustness, whereas through-wall radar focuses on the balance between accuracy and generalization ability in walled scenarios, and WiFi signals show unique value in the smart home and security fields.The study points out that current technology faces challenges such as signal sparsity, insufficient cross-modal generalization, and high hardware cost, and explores typical application scenarios such as medical, healthcare, and industrial security.Future research can focus on self-supervised multimodal fusion, privacy-preserving frameworks, and dynamic adaptive algorithms, laying the technical foundation for 6G communication-sensing integration..