Accurate Step Length Estimation for Pedestrian Dead Reckoning Localization Using Stacked Autoencoders
Accurate Step Length Estimation for Pedestrian Dead Reckoning Localization Using Stacked Autoencoders is a scholarly work, published in 2019 in ''IEEE Transactions on Instrumentation and Measurement''. The main subjects of the publication include pedestrian, data mining, artificial intelligence, computer vision, Speech enhancement, dead reckoning, indoor positioning system, lock, Multiple object tracking, project management estimation, phone, machine learning, computer science, and independent events. To solve these problems, authors propose a deep learning-based step length estimation model, which can adapt to different phone carrying ways and does not require individual stature information and spatial constraints.