A CSI Dataset for Wi-Fi-based Personnel Identity Recognition

This dataset utilizes Asus RT-AC86U routers and nexmon tools to collect Channel State Information (CSI) data in a 7 by 5 meters meeting room furnished with typical furniture including a conference table, several chairs, and a locker. The data, stored in .pcap format, is accompanied by processing code on GitHub, enabling parsing into CSI matrix data stored in .npy format. Each CSI matrix contains amplitude and processed phase values for four channels, encompassing data from both external and internal antennas within the room. These matrices facilitate in-depth analysis of dynamic changes in the wireless channel induced by human movement, serving as a resource for research in human activity recognition and related fields.本数据集采用华硕（Asus）RT-AC86U路由器与nexmon工具，在一间7米×5米的会议室中采集信道状态信息（Channel State Information，CSI）数据。该会议室配备典型办公家具，包含会议桌、若干座椅与储物柜。采集所得数据以.pcap格式存储，附带GitHub平台上的处理代码，可将其解析为存储于.npy格式中的CSI矩阵数据。每一份CSI矩阵均包含四个信道的幅度值与经处理的相位值，覆盖本次实验中会议室内置与外置天线采集的全部数据。此类矩阵可用于深入分析人体移动引发的无线信道动态变化，可作为人类活动识别及相关领域的研究资源。

搜集汇总

背景与挑战

背景概述

该数据集基于Wi-Fi信道状态信息（CSI）用于人员身份识别，在7x5米会议室中通过Asus RT-AC86U路由器采集，存储为.pcap格式，并配套预处理代码可解析为包含振幅和相位的CSI矩阵。数据集包含多人随机移动的CSI测量及参与者详细信息，适用于无线信道动态分析和人员身份识别等相关研究。