Multi-Information Fusion Indoor Localization Using Smartphones

Accurate indoor localization estimation has important social and commercial values, such as location services pedestrian retention times. Acoustic-based methods can achieve high accuracies in specific scenarios with special equipment; however, it is a challenge to obtain accurate general equipment environments. To solve this problem, we propose novel fusion CHAN the improved dead reckoning (PDR) system (CHAN-IPDR-ILS). In system, step length method that adds previous two steps for extracting more information estimate current length. The maximum influence factor set ensure importance of We also heading direction correction mitigate errors sensor data. Finally, achieved using motion model acoustic dynamic PDR estimation. localization, threshold confidence level distance between base-acoustic are accidental cumulative errors. experiments were performed at trial sites different users, devices, scenarios, experimental results demonstrate proposed higher accuracy compared state-of-the-art methods. manages heterogeneity provides generality flexibility devices low cost.