Wearable Indoor Pedestrian Navigation Based on MIMU and Hypothesis Testing
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Chao Li | Xu Zhao | Zhong Su | Fuchao Liu | Xiao-fei Ma | C. Li | Fuchao Liu | Zhong Su | Xu Zhao | Xiaofei Ma
[1] Xiaoli Ma,et al. Eigenvector-based initial ranging process for OFDMA uplink systems , 2015, EURASIP Journal on Advances in Signal Processing.
[2] Alessio De Angelis,et al. A constraint approach for UWB and PDR fusion , 2012, 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN).
[3] Isaac Skog,et al. Zero-Velocity Detection—An Algorithm Evaluation , 2010, IEEE Transactions on Biomedical Engineering.
[4] Fernando Seco Granja,et al. Robust indoor positioning fusing PDR and RF technologies: The RFID and UWB case , 2013, International Conference on Indoor Positioning and Indoor Navigation.
[5] Fernando Seco Granja,et al. Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU , 2010, 2010 7th Workshop on Positioning, Navigation and Communication.
[6] Eric Foxlin,et al. Pedestrian tracking with shoe-mounted inertial sensors , 2005, IEEE Computer Graphics and Applications.
[7] Isaac Skog,et al. Evaluation of zero-velocity detectors for foot-mounted inertial navigation systems , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.
[8] Hao Jiang,et al. Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization , 2015, Sensors.
[9] Henri Nurminen,et al. Kalman filter with a linear state model for PDR+WLAN positioning and its application to assisting a particle filter , 2015, EURASIP J. Adv. Signal Process..
[10] Hiroyuki Yokoyama,et al. Estimating Position Relation between Two Pedestrians Using Mobile Phones , 2012, Pervasive.