Acoustic Self-Calibrating System for Indoor Smart Phone Tracking. (26th February 2015)

• Record Type: Journal Article
• Authors: Ens, Alexander; Höflinger, Fabian; Wendeberg, Johannes; Hoppe, Joachim; Zhang, Rui; Bannoura, Amir; Reindl, Leonhard M.; Schindelhauer, Christian
• Other Names: Dogandzic Aleksandar Academic Editor.
• Is Part Of: International journal of navigation and observation. Volume 2015(2015)
• Publication Date: 2015-02-26
• Subjects: Navigation -- Periodicals; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Global Positioning System -- Periodicals; Earth sciences -- Periodicals; Environmental monitoring -- Periodicals; Navigation; Télédétection; Systèmes d'information géographique; GPS; Sciences de la terre; Environnement -- Surveillance; Earth sciences; Environmental monitoring; Geographic information systems; Global Positioning System; Navigation; Remote sensing; Periodicals; Electronic journals; 629.045
• DOI: 10.1155/2015/694695
• Languages: English
• ISSNs: 1687-5990

Abstract

Abstract : This paper presents an acoustic indoor localization system for commercial smart phones that emit high pitched acoustic signals beyond the audible range. The acoustic signals with an identifier code modulated on the signal are detected by self-built receivers which are placed at the ceiling or on walls in a room. The receivers are connected in a Wi-Fi network, such that they synchronize their clocks and exchange the time differences of arrival (TDoA) of the received chirps. The location of the smart phone is calculated by TDoA multilateration. The precise time measuring of sound enables high precision localization in indoor areas. Our approach enables applications that require high accuracy, such as finding products in a supermarket or guiding blind people through complicated buildings. We have evaluated our system in real-world experiments using different algorithms for calibration-free localization and different types of sound signals. The adaptive GOGO-CFAR threshold enables a detection of 48% of the chirp pulses even at a distance of 30 m. In addition, we have compared the trajectory of a pedestrian carrying a smart phone to reference positions of an optic system. Consequently, the localization error is observed to be less than 30 cm.