This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the mobile device is not required. To resolve the data insufficiency problem, flow control signals such as request to send (RTS) and clear to send (CTS) are utilized. In our model, received signal strength indicator (RSSI) and channel state information (CSI) are used as fingerprints for several algorithms, including deterministic, probabilistic and neural networks localization algorithms. We further investigated localization algorithms performance through extensive on-site experiments with various models of phones at hundreds of testing locations. We demonstrate that our passive scheme achieves an average localization error of 0.8 m when the phone is actively transmitting data frames and 1.5 m when it is not transmitting data frames.
翻译:本文建议采用被动的无线网络内部定位。 我们不使用移动设备收到的无线网络信号作为指纹,而是使用路由器收到的信号来定位移动承运人。 因此,不需要在移动设备上安装软件。 为解决数据不足问题,使用流动控制信号,如要求发送(RTS)和明确发送(CTS)等流动控制信号。 在我们的模型中,接收的信号强度指标(RSSI)和频道状态信息(CSI)被用作若干算法的指纹,包括确定性、概率和神经网络的本地化算法。 我们进一步通过在数百个测试地点与各种电话模型进行广泛的现场实验来调查本地化算法的性能。 我们证明,当电话正在积极传输数据框架时,我们的被动方案实现了0.8米的平均本地化错误,而没有传输数据框架时则实现了1.5米的平均本地化错误。