Abstract
Beacons using bluetooth low-energy (BLE) technology have emerged as a new paradigm of indoor positioning service (IPS) because of their advantages such as low power consumption, miniaturization, wide signal range, and low cost. However, the beacon performance is poor in terms of the indoor positioning accuracy because of noise, motion, and fading, all of which are characteristics of a bluetooth signal and depend on the installation location. Therefore, it is necessary to improve the accuracy of beacon-based indoor positioning technology by fusing it with existing indoor positioning technology, which uses Wi-Fi, ZigBee, and so forth. This study proposes a beacon-based indoor positioning method using an extended Kalman filter that recursively processes input data including noise. After defining the movement of a smartphone on a flat two-dimensional surface, it was assumed that the beacon signal is nonlinear. Then, the standard deviation and properties of the beacon signal were analyzed. According to the analysis results, an extended Kalman filter was designed and the accuracy of the smartphone’s indoor position was analyzed through simulations and tests. The proposed technique achieved good indoor positioning accuracy, with errors of 0.26 m and 0.28 m from the average x- and y-coordinates, respectively, based solely on the beacon signal.
Highlights
Location determination technology in smartphones equipped with global positioning system (GPS) and Wi-Fi has triggered a shift in the paradigm of locationbased services (LBS) and contributed significantly toward the further development of such services, including navigation and logistics [1, 2]
Indoor positioning techniques previously adopted by indoor positioning service (IPS) include the K-nearest neighbor, Bayesian, and triangulation methods, which are based on wireless technologies such as Wi-Fi, radio frequency identification (RFID), and ZigBee [3,4,5,6]
Following the launch of iBeacon, Apple applied it to a mobile payment service that replaced near field communication and to a service that provides information on matches held at the stadiums of the Boston Red Sox, LA Dodgers, and so forth
Summary
Location determination technology in smartphones equipped with global positioning system (GPS) and Wi-Fi has triggered a shift in the paradigm of locationbased services (LBS) and contributed significantly toward the further development of such services, including navigation and logistics [1, 2]. Indoor positioning techniques previously adopted by IPS include the K-nearest neighbor, Bayesian, and triangulation methods, which are based on wireless technologies such as Wi-Fi, radio frequency identification (RFID), and ZigBee [3,4,5,6]. Recent studies have focused on an ultrawideband-based indoor positioning technology [7, 8]. Beacons have contributed toward the growth of mobile LBS and emerged as a new paradigm of IPS. Their advantages include low power consumption, miniaturization, wide signal range, and low cost. When communicating with devices as far away as 70 m, the accuracy of BLE is sufficiently high for distinguishing each device with a resolution of 5–10 cm [9,10,11]
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