FIND: an SDR-based Tool for Fine Indoor Localization

TL;DR

FIND is a novel SDR-based tool that accurately estimates Wi-Fi signal directions indoors by extracting comprehensive frame data in real-time, supporting advanced localization research.

Contribution

It introduces the first prototype capable of real-time DoA estimation from Wi-Fi frames using SDR, with a new calibration method and publicly available dataset.

Findings

First real-time Wi-Fi DoA estimation prototype using SDR

Provides comprehensive frame data including preamble, CSI, and SNR

Offers datasets for indoor localization research

Abstract

An indoor localization approach uses Wi-Fi Access Points (APs) to estimate the Direction of Arrival (DoA) of the WiFi signals. This paper demonstrates FIND, a tool for Fine INDoor localization based on a software-defined radio, which receives Wi-Fi frames in the 80 MHz band with four antennas. To the best of our knowledge, it is the first-ever prototype that extracts from such frames data in both frequency and time domains to calculate the DoA of Wi-Fi signals in real-time. Apart from other prototypes, we retrieve from frames comprehensive information that could be used to DoA estimation: all preamble fields in the time domain, Channels State Information, and signal-to-noise ratio. Using our device, we collect a dataset for comparing different algorithms estimating the angle of arrival in the same scenario. Furthermore, we propose a novel calibration method, eliminating the constant phase shift between receiving paths caused by hardware imperfections. All calibration data, as well as a gathered dataset with various DoA in an anechoic chamber and in a classroom, are provided to facilitate further research in the area of indoor localization, intelligence surfaces, and multi-user transmissions in dense deployments.