WiFi Indoor Localization Using Channel State Information

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Abstract

Indoor positioning has several variants as a result of multiple years of study on the topic. Using WiFi signals as the technology to compute the position of the target device is one of the most extended and researched techniques. WiFi Access Points are extensively deployed in all indoor environments where WiFi indoor localization has a potential application. Several of these indoor localization techniques use the Received Signal Strength (RSS) to compute the location of the device. However, the accuracy of the methods that use this parameter is usually low, in the meter range. Eight years ago, the new advances in wireless communications allowed to retrieve the phase of an incoming signal from a commercial chipset, and not only its strength. With the phase, we can use the physical and mathematical principles of signal transmission to compute the distance to a device. In the long term, it can contribute to having a more robust and long-lasting method to perform indoor localization if we can overcome the challenge of obtaining a delay-free phase measurement. For indoor distances, a small delay in the time estimation can be translated into a significant error in the ranging result. In this work, we re-implement the ranging technique of the paper Chronos: Decimeter-Level Localization with a Single WiFi Access Point. This well-known research work explains how to obtain an accurate phase measurement from a WiFi chipset and the technique to compute the distance to the target. We provide a guide of the installation and implementation of the hardware and software required for a system like this, indicating the critical points to allow future researchers a quick set up of the equipment. We revisit the procedure of Chronos to obtain a delay-free phase measurement and show how to re-implement it from scratch. Finally, we perform a validation of the system in four different steps, from the use of ideal data to progressively introducing the real distortions of indoor wireless data. The evaluation of the performance of the system leads us to present the finding of a non-linear delay that can produce significant distance errors.