RAPID：改造IEEE 802.11ay接入点以实现室内人体检测与感知
RAPID: Retrofitting IEEE 802.11ay Access Points for Indoor Human Detection and Sensing
AI总结：
本研究提出基于60 GHz IEEE 802.11ay WiFi的RAPID系统，利用波束训练与跟踪提取微多普勒特征，结合深度学习实现高精度人体感知，无需专用传感器与修改标准包结构，性能优于现有亚6GHz方案。
摘要：
在本研究中，我们提出了RAPID，这是首个基于工作在60 GHz频段的下一代IEEE 802.11ay WiFi网络的通信与雷达联合系统。与现有的毫米波人体感知方法依赖专用雷达不同，RAPID利用IEEE 802.11ay接入点即可达到雷达级的感知精度，从而免去了安装专用传感器的负担。RAPID无需修改标准数据包结构，便可支持非接触式人体感知应用，例如人员追踪、人类活动识别（Human Activity Recognition, HAR）以及身份识别。具体而言，我们利用IEEE 802.11ay的波束训练功能，对同一环境内的多个个体进行精确定位与追踪。随后，我们提出了一种利用波束跟踪的新方法，从反射数据包估计得到的时变信道冲激响应（Channel Impulse Response, CIR）中提取微多普勒特征。这些特征被输入深度学习分类器，以执行HAR和身份识别任务。RAPID在配备相控天线阵列的前沿IEEE 802.11ay兼容FPGA平台上实现，并在大型CIR测量数据集上进行了评估。它在不同环境和受试者中均具有鲁棒性，性能优于现有的6 GHz以下WiFi感知技术。使用两个接入点时，RAPID可可靠追踪多个受试者，其HAR和身份识别准确率分别达到94%和90%。
英文摘要：
In this work we present RAPID, the first joint communication and radar system based on next-generation IEEE 802.11ay WiFi networks operating in the 60 GHz band. Unlike existing approaches for human sensing at millimeter-wave frequencies, which rely on special-purpose radars, RAPID achieves radar-level sensing accuracy with IEEE 802.11ay access points, thus avoiding the burden of installing ad-hoc sensors. RAPID enables contactless human sensing applications, such as people tracking, Human Activity Recognition (HAR), and person identification without requiring modifications to the standard packet structure. Specifically, we leverage IEEE 802.11ay beam training to accurately localize and track multiple individuals within the same environment. Then, we propose a new way of using beam tracking to extract micro-Doppler signatures from the time-varying Channel Impulse Response (CIR) estimated from reflected packets. Such signatures are fed to a deep learning classifier to perform HAR and person identification. RAPID is implemented on a cutting-edge IEEE 802.11ay-compatible FPGA platform with phased antenna arrays, and evaluated on a large dataset of CIR measurements. It is robust across different environments and subjects, and outperforms state-of-the-art sub-6 GHz WiFi sensing techniques. Using two access points, RAPID reliably tracks multiple subjects, reaching HAR and person identification accuracies of 94% and 90%, respectively.
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