Smartphone-Based Indoor Integrated WiFi/MEMS Positioning Algorithm in a Multi-Floor Environment

Smartphone-Based Indoor Integrated WiFi/MEMS Positioning Algorithm in a Multi-Floor Environment

Blog Article

Indoor positioning in a multi-floor environment by using a smartphone is considered in this paper.The positioning accuracy and robustness of WiFi fingerprinting-based positioning are limited due to the unexpected variation of WiFi measurements between floors.On this basis, we propose a novel smartphone-based integrated WiFi/MEMS positioning algorithm based on the robust extended Kalman Private Keeping of Dangerous Wild Animals in Great Britain filter (EKF).The proposed algorithm first relies on the gait detection approach and quaternion algorithm to estimate the velocity and heading angles of the target.

Second, the velocity and heading angles, together with the results of WiFi fingerprinting-based positioning, are considered as the input of the robust EKF for the sake of conducting two-dimensional (2D) positioning.Third, the proposed algorithm calculates A supervised scheme for aspect extraction in sentiment analysis using the hybrid feature set of word dependency relations and lemmas the height of the target by using the real-time recorded barometer and geographic data.Finally, the experimental results show that the proposed algorithm achieves the positioning accuracy with root mean square errors (RMSEs) less than 1 m in an actual multi-floor environment.