Multi-sensor data fusion for indoor drone positioning

Yufeng Chen; Jintao Ding

doi:10.1117/12.2687168

21 July 2023 Multi-sensor data fusion for indoor drone positioning

Yufeng Chen, Jintao Ding

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 1271709 (2023) https://doi.org/10.1117/12.2687168
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

The positioning of indoor mobile machines cannot be solved by a single sensor. A positioning system based on multi-sensor data fusion is designed. The system combines the positioning results of UWB with the positioning results of low-cost MEMS inertial measurement elements to improve the positioning accuracy of the system. The system includes two Kalman filters. The primary Kalman filter is used to fuse the angular velocity information of gyroscope and the angular value of magnetometer, so as to obtain more accurate heading angle. The secondary Kalman filter combines the IMU track estimation results with the UWB positioning results to obtain accurate positioning results. The final experimental results show that the method is effective.

Citation Download Citation

Yufeng Chen and Jintao Ding "Multi-sensor data fusion for indoor drone positioning", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 1271709 (21 July 2023); https://doi.org/10.1117/12.2687168

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