A Wi-Fi RTT/data-driven inertial navigation pedestrian indoor positioning method
In pursuit of investigating pedestrian indoor positioning methods based on smartphones and enhancing the precision of indoor pedestrian localization,this paper proposes a localization system utilizing Wi-Fi RTT and IMU for the indoor positioning of pedestrians using smartphones.The method comprises three key components:①The introduction of a Wi-Fi RTT indoor positioning method that employs extended Kalman filtering to integrate distance measurement information.②The proposition of a dead reckoning method suitable for multi-phone usage,utilizing LSTM to establish a neural network model for predicting pedestrian movement speed and heading.③The development of a fusion positioning method based on ESKF that combines Wi-Fi RTT and data-driven inertial navigation to further elevate positioning accuracy.Experimental findings illustrate that,in comparison to individual Wi-Fi RTT and data-driven inertial navigation methods,the proposed approach achieves an average improvement of 10%to 20%in positioning accuracy.
万方数据
维普
