A comparison of Pedestrian Dead-Reckoning algorithms using a low-cost MEMS IMU

By A. Jiménez, F. Seco, C. Prieto, J. Guevara. IEEE International Symposium on Intelligent Signal Processing,, 2009

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A Survey of Indoor Inertial Positioning Systems for Pedestrians (2013, background): “Even magnetometer thresholding can give usable stance detection under some circumstances [19].”
WILL: Wireless indoor localization without site survey (2012, methodology): “To avoid accumulation of measurement errors, most researchers adopt the individual step counts for estimating walking distance, just like a pedometer [24].”
Smartphones Based Crowdsourcing for Indoor Localization (2015, methodology): “We employ a local variance threshold method [13] to detect the number of steps.”
Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements (2012, methodology): “In [24], [25], [30] a INS-based PDR method is updated with position and velocity estimations from a parallel RFID probabilistic fingerprinting positioning method.”
Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU (2010, background): “They properly work in many situations but occasionally fail in slow and random walk [13].”
Locating in fingerprint space: wireless indoor localization with little human intervention (2012, methodology): “We employ a local variance threshold method [13] to detect the number of steps.”