Martin, 2018, Positioning technologies in location-based services, 15
Wu, 2019, A survey of the research status of pedestrian dead reckoning systems based on inertial sensors, Int. J. Autom. Comput., 16, 65, 10.1007/s11633-018-1150-y
Wang, 2018, Pedestrian dead reckoning based on motion mode recognition using a smartphone, Sensors, 18, 1811, 10.3390/s18061811
Hsu, 2018, Indoor localization and navigation using smartphone sensory data, Ann. Oper. Res., 265, 187, 10.1007/s10479-017-2398-2
Kammoun, 2015, An efficient fuzzy logic step detection algorithm for unconstrained smartphones, 2110
Zhang, 2018, Pedestrian dead-reckoning indoor localization based on os-elm, IEEE Access, 6, 6116, 10.1109/ACCESS.2018.2791579
Diez, 2018, Step length estimation methods based on inertial sensors: A review, IEEE Sens. J., 18, 6908, 10.1109/JSEN.2018.2857502
Zhou, 2016, Pedestrian dead reckoning on smartphones with varying walking speed, 1
Díez, 2015, Signal processing requirements for step detection using wrist-worn imu, 1032
Sushil Tiwari, Vinod Kumar Jain, Smartphone Based Improved Floor Determination Technique for Multi-Floor Buildings, in: Proceedings of the World Congress on Engineering, London, UK, 2018, pp. 4–6.
Martinelli, 2017, Probabilistic context-aware step length estimation for pedestrian dead reckoning, IEEE Sens. J., 18, 1600, 10.1109/JSEN.2017.2776100
Hung, 2010, A new weighted fuzzy c-means clustering algorithm for remotely sensed image classification, IEEE J. Sel. Top. Sign. Proces., 5, 543, 10.1109/JSTSP.2010.2096797