Robust Stride Detector from Ankle-Mounted Inertial Sensors for Pedestrian Navigation and Activity Recognition with Machine Learning Approaches by Bertrand Beaufils, Frédéric Chazal, Marc Grelet, Bertrand Michel

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Optimal Heading Estimation Based Multidimensional Particle Filter for Pedestrian Indoor Positioning by Ling Pei, Donghui Liu, Danping Zou, Ronald Lee Fook Choy, Yuwei Chen, Zhe He

“…Alternatively, today’s smartphones have an increased number of integrated sensors that can act as terminals for indoor personal positioning solutions such as pedestrian dead reckoning (PDR). However, magnetic interference, poor sensor measurements, and diverse handling of smartphone quickly decrease the performance for indoor PDR. …”
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Analyzing Gait in the Real World Using Wearable Movement Sensors and Frequently Repeated Movement Paths by Weixin Wang, Peter Gabriel Adamczyk

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Smartphone-Based Unconstrained Step Detection Fusing a Variable Sliding Window and an Adaptive Threshold by Ying Xu, Guofeng Li, Zeyu Li, Hao Yu, Jianhui Cui, Jin Wang, Yu Chen

“…Step detection for smartphones plays an important role in the pedestrian dead reckoning (PDR) for indoor positioning. …”
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Indoor Positioning System Based on Chest-Mounted IMU by Chuanhua Lu, Hideaki Uchiyama, Diego Thomas, Atsushi Shimada, Rin-ichiro Taniguchi

“…Therefore, we propose a novel regression model for estimating step lengths only with accelerations to correctly compute step displacement by using the IMU data acquired at the chest. …”
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A Multi-Mode PDR Perception and Positioning System Assisted by Map Matching and Particle Filtering by Xuan Wang, Guoliang Chen, Mengyi Yang, Saizhou Jin

“…Currently, pedestrian dead reckoning (PDR) is widely used in indoor positioning. …”
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Pedestrian Stride-Length Estimation Based on LSTM and Denoising Autoencoders by Qu Wang, Langlang Ye, Haiyong Luo, Aidong Men, Fang Zhao, Yan Huang

“…Accurate stride-length estimation is a fundamental component in numerous applications, such as pedestrian dead reckoning, gait analysis, and human activity recognition. …”
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Foot-Mounted Pedestrian Navigation Method by Comparing ADR and Modified ZUPT Based on MEMS IMU Array by Li Xing, Xiaowei Tu, Zhi Chen

“…Then, by using the step length and the track angle of each step computed by remaining IMUs, the foot position extracted from the traditional ZUPT model is estimated on the basis of least squares (LS) so as to improve the traveled distance calculation accuracy. …”
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On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System by Wen-Yuah Shih, Kun-Chan Lan

“…Some prior studies proposed the use of Pedestrian Dead Reckoning (PDR) for indoor localization, which does not require the deployment of beacon nodes. …”
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A Bluetooth/PDR Integration Algorithm for an Indoor Positioning System by Xin Li, Jian Wang, Chunyan Liu

“…As to the PDR approach, a more effective multi-threshold step detection algorithm is used to improve the positioning accuracy. …”
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Pedestrian Navigation Based on a Waist-Worn Inertial Sensor by Rafael C. González, Antonio López, Diego Alvarez, Juan Carlos Alvarez

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Integrating Moving Platforms in a SLAM Agorithm for Pedestrian Navigation by Susanna Kaiser, Christopher Lang

“…In this work, we integrate the MPs in an upper 3D-simultaneous localization and mapping (SLAM) algorithm which is cascaded to the pedestrian dead-reckoning (PDR) technique. The step and heading measurements resulting from the PDR are fed to the SLAM that additionally estimates a map of the environment during the walk in order to reduce the remaining drift. …”
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Integrated WiFi/PDR/Smartphone Using an Adaptive System Noise Extended Kalman Filter Algorithm for Indoor Localization by Xin Li, Jian Wang, Chunyan Liu, Liwen Zhang, Zhengkui Li

“…Wi-Fi fingerprint matching typically requires a quite high computational burden: To reduce the computational complexity of this step, the affinity propagation clustering algorithm is adopted to cluster the fingerprint database and integrate the information of the position domain and signal domain of respective points. …”
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Body-Centered Dynamically-Tuned Error-State Extended Kalman Filter for Visual Inertial Odometry in GNSS-Denied Environments by Shaza I. Kaoud Abdelaziz, Haidy Y. Elghamrawy, Aboelmagd M. Noureldin, Georgia Fotopoulos

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A Probabilistic Method-Based Smartphone GNSS Fault Detection and Exclusion System Utilizing PDR Step Length by Changhui Jiang, Yuwei Chen, Zuoya Liu, Qingyuan Xia, Chen Chen, Juha Hyyppa

“…Firstly, an optimized particle filter method employing a Krill Herd Algorithm (KHA) is suggested for the integration of GNSS and Pedestrian Dead Reckoning (PDR). Secondly, a probabilistic approach is presented to identify faulty GNSS measurements using step distance information obtained from the PDR. …”
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Research on Pedestrian Indoor Positioning Based on Two-Step Robust Adaptive Cubature Kalman Filter with Smartphone MEMS Sensors by Jijun Geng, Xuexiang Yu, Congcong Wu, Guoqing Zhang

“…In addition, based on the accelerometer information, a nonlinear model is constructed and the empirical model is used to estimate the step length. Combining heading and step length, the two-step robust-adaptive-cubature Kalman filter is proposed to improve the pedestrian-dead-reckoning method, which enhances the adaptability and robustness of the algorithm and further improves the accuracy of the plane-position solution. …”
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An optimal innovation based adaptive estimation Kalman filter for accurate positioning in a vehicular ad-hoc network by Sumithra S., Vadivel R.

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Design of personnel positioning system in coal mine underground based on MEMS sensor by ZHAO Yue, LAN Ying, QU Xian

“…It combines with pedestrian dead reckoning (PDR) algorithm and through existing underground WiFi base station to realize accurate positioning for underground personnel: it uses an expression that combined the variance of the walking frequency and acceleration to determine step length, and uses the quaternion method to estimated pedestrian orientation angle, uses extended Kalman filter to correct the original data, so as to obtain specific location of underground personnels. …”
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Using Step Size and Lower Limb Segment Orientation from Multiple Low-Cost Wearable Inertial/Magnetic Sensors for Pedestrian Navigation by Chandra Tjhai, Kyle O’Keefe

“…This research looks at the problem of pedestrian navigation in a practical manner by investigating dead-reckoning methods using low-cost sensors. This work uses the estimated sensor orientation angles to compute the step size from the kinematics of a skeletal model. …”
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A Robust Step Detection Algorithm and Walking Distance Estimation Based on Daily Wrist Activity Recognition Using a Smart Band by Duong Trong Bui, Nhan Duc Nguyen, Gu-Min Jeong

“…Human activity recognition and pedestrian dead reckoning are an interesting field because of their importance utilities in daily life healthcare. …”
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