FLoc: Device-free passive indoor localization in complex environments

Localization in complex indoor environments with RF signal is a challenging task. Via this technique, the signal is easily affected by obstacles and environmental noise due to the broadcast nature of RF signal transmission. In this paper, we observe that seismic signal is more oriented than the RF signal, and thus is more suitable for localization in an complex indoor environment with obstacles. Motivated by this observation, we propose a device-free passive indoor localization system, namely Floc, that can fight against environmental impact and achieve high localization accuracy. FLoc is composed of three modules, which are sensing module that collects seismic signal from footsteps, footstep detection module that remove the environmental impact and recover the clean footsteps, and localization module that leverages seismic signal from footsteps for positioning. We implement FLoc on credit-card sized single-board computer Raspberry Pi equipped with geophones. To verify the effectiveness of our system, we conduct extensive experiments for different scenario in a complex indoor environment with the area of 6 × 8 square meter. The experimental results demonstrates that Floc can achieve up to 7cm localiztion accuracy on average, and can outperform the existing acoustic signal-based localization techniques.

I. Introduction

Indoor localization is currently a cutting-edge research topic because of its huge market value. Extensive research has been carried out in this direction. Till now, numerous technologies, such as infrared, Bluetooth, Computer Vision, RFID, WiFi, ZigBee, Ultra Wide Band (UWB), etc. are used to address this problem. Among these technologies, UWB and infrared have the highest positioning precision. However, UWB has high cost and infrared technology has blocking issue. Cameras cannot be applied in intelligent home environments because of privacy issues. Consequently, RF signaling technology is the most popular at this point. However, the transmission of RF signal is broadcast by nature, and the receiver receives the signal after multiple reflection in 3D space. As shown in the top half of Fig. 1, a human voice is received by a microphone from different paths at different time instants.