Acoustic Self-calibrating System for Indoor Smartphone Tracking (ASSIST)

In this paper, we present a novel smartphone indoor localization system. The smartphone user is localized with small effort, affordable equipment and with high accuracy in indoor areas. The system uses commercially available smartphones generating high pitched acoustic chirp signals beyond the audible range. The chirp signals are received by sound receivers which identify the specific sound produced from each smartphone. The receivers are connected to a WiFi network, such that they synchronize their clocks and exchange the time differences of arrival (TDoA) of the received chirps. In this way, using an iterative multilateration algorithm, the location of the smartphones can be calculated and the receiver positions are calibrated automatically. For generating the specific sound signals from the smartphone and for user navigation an Android software application was developed. The user interface is simple and is invoked by starting the software application, which automatically connects to a server and receives an ID using the internet connection of the smartphone. Furthermore, the user is assigned specific parameters, such that several devices can be distinguished by the appearance of the chirps. The position of the user is displayed on the smartphone in context of the environment, with a map and surrounding items. In the presented work we have verified our system in a real-world scenario. We compared our trajectory of a pedestrian carrying smartphone to the reference positions. We could locate the smartphones with error margin of 30 cm. a centimeter margin of error.