Research Article
Adaptive fusion localization mechanism towards TDoA and IMU data with LSTM correction Method
@INPROCEEDINGS{10.4108/eai.29-6-2019.2282992, author={Zhiyuan Liu and Liang Li and Zheng Wang and Chen Ao and Qiang Fu and Puning Zhang}, title={Adaptive fusion localization mechanism towards TDoA and IMU data with LSTM correction Method}, proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2019}, month={6}, keywords={fusion positioning tdoa imu adaptive kalman filter lstm}, doi={10.4108/eai.29-6-2019.2282992} }- Zhiyuan Liu
Liang Li
Zheng Wang
Chen Ao
Qiang Fu
Puning Zhang
Year: 2019
Adaptive fusion localization mechanism towards TDoA and IMU data with LSTM correction Method
MOBIMEDIA
EAI
DOI: 10.4108/eai.29-6-2019.2282992
Abstract
Using Time Difference of Arrival(TDoA) positioning results and the Inertial measurement unit(IMU) for calculating the motion state of information fusion can significantly improve the positioning accuracy, due to the carrier in the process of movement, the state of the system noise and measurement noise are not strictly obey the normal gaussian distribution, which makes the traditional fusion positioning method using Kalman Filtering algorithm less accurate. This paper proposes an adaptive filter fusion localization mechanism with LSTM network correction. Firstly, a data preprocessing method is designed to convert IMU data from the carrier coordinate system to the geographical coordinate system. Then, based on kinematics theory, the state equation and measurement equation of Adaptive Kalman Filter are established and the system state noise is obtained. Furthermore, the model adaptively to update the carrier coordinate, system state noise and measurement noise. Finally, the carrier trajectory coordinates predicted by the coupled LSTM model are used to obtain the final positioning results and complete the carrier trajectory filtering. Experimental results show that the proposed fusion localization mechanism can effectively improve the accuracy of carrier trajectory localization.
