Journal Article10.1016/j.aeue.2023.154674
An improved pedestrian dead reckoning algorithm based on smartphone built-in MEMS sensors
01 Aug 2023
Vol. 168, pp 154674-154674
3
About: The article was published on 01 Aug 2023. The article focuses on the topics: Dead reckoning & Pedestrian.
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Citations
Beamforming Optimization of Linear and Planar Antenna Array Using a New Algorithm Based on the Corrosion Diffusion Behavior
Hussien A. Al-mtory,Falih M. Alnahwi,Ramzy S. Ali +2 more
Research on Pedestrian Dead Reckoning Algorithm with Feature Constraints
SuQing Yan,Xiao Huang,Xiao Jianming,Yuanfa Ji,Qiang Fu,Kamarul Hawari Bin Ghazali,SuQing Yan,Xiao Huang,Xiao Jianming,Yuanfa Ji,Qiang Fu,Kamarul Hawari Bin Ghazali +11 more
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PDR Heading Elasticity Compensation Method Based on Modal Identification
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- 01 Mar 2024
TL;DR: A PDR heading elasticity compensation method based on modal identification effectively improves heading accuracy under multiple motion modes of pedestrians.
References
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TL;DR: The proposed fusion method achieves remarkable improvement in scalability and precision in both static and dynamic tests, including outdoor and indoor environments, and achieves an average positioning accuracy of 1.435 m with an update rate of every 0.19 s.
LSTM-Based Zero-Velocity Detection for Robust Inertial Navigation.
Brandon Wagstaff,Jonathan Kelly +1 more
TL;DR: In this paper, the authors proposed a method to improve the accuracy of a zero-velocity-aided inertial navigation system (INS) by replacing the standard zerovelocity detector with a long short-term memory (LSTM) neural network.
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A Robust Step Detection and Stride Length Estimation for Pedestrian Dead Reckoning Using a Smartphone
TL;DR: A dynamic time warping–based peak prediction with zero-crossing detection to improve the SD accuracy and an improved SLE model is proposed for the different walking patterns to achieve a higher SLE accuracy.
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WiFi-Aided Magnetic Matching for Indoor Navigation with Consumer Portable Devices
TL;DR: The results supported that the WiFi-aided MM algorithm provided more reliable solutions than both WiFi and MM in the areas that have poor WiFi signal distribution or indistinctive magnetic-gradient features.
Indoor Positioning Based on Pedestrian Dead Reckoning and Magnetic Field Matching for Smartphones.
TL;DR: An ambient magnetic field map-based matching (MM) positioning algorithm for smartphones in an indoor environment using a magnetic field sequence combined with the measured trajectory contour coming from pedestrian dead-reckoning (PDR) is presented.
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