Hybrid Wireless Positioning

Abstract: Numerous location-based services (LBS) have evolved because of the fast development of mobile Internet for use in commerce, entertainment, security, and other areas. All of these need a precise real-time location-based service with smooth indoor- outdoor transition in highly populated areas. A truly omnipresent location system for both indoor and outdoor settings is still not accessible, despite the global navigation satellite system (GNSS) technology enabling excellent outdoor location services. To find a solution for the indoor-outdoor transition accuracy, we suggest a solution of hybrid positioning system (HPS) that combines the position data of Bluetooth Low Energy (BLE) Beacon and the GNSS technology. This work investigates a BLE-GNSS Hybrid positioning scheme based on AOA (Angle of Arrival) obtained by BLE and GNSS position estimate. The fusion algorithms tested here are the Weighted-Least square (WLS) method and the Kalman filter (KF) method. At the end of the investigation, we draw a comparison between these two fusion algorithms, and the results in the indoor-outdoor environment show that the proposed solution based on WLS improves the accuracy by up to 22% while the one based on KF enhances the accuracy by up to 38% compared to BLE performance, in the same environment the performance is improved compared with GNSS, HPS based on Kalman filter improves the accuracy up to 62% and HPS based in WLS improves the accuracy up to 31%. Keywords: Global Navigation Satellite System (GNSS), Bluetooth Low Energy (BLE), Hybrid Positioning System (HPS), Fusion Algorithms.