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UWB/MEMS IMU integrated positioning method based on NLOS angle discrimination and MAP constraints
Xin Sui1, Jiapeng Song2, Changqiang Wang1
1School of Geomatics, Liaoning Technical University, Fuxin, 123000, China.
Scientific Reports
|August 27, 2024
Summary
This study introduces a dynamic non-line-of-sight (NLOS) angle discrimination method for ultrawideband (UWB) signals. The novel algorithm improves UWB/MEMS IMU positioning accuracy in dynamic, occluded environments.
Area of Science:
- Navigation and Positioning Systems
- Signal Processing
- Robotics and Autonomous Systems
Background:
- Ultrawideband (UWB) signals face localization challenges in dynamic environments due to non-line-of-sight (NLOS) conditions and signal occlusion.
- Existing NLOS error characterization for UWB signals in dynamic settings is insufficient, hindering reliable positioning.
- Signal occlusion significantly impacts UWB ranging accuracy, especially at specific horizontal angles.
Purpose of the Study:
- To propose a dynamic NLOS angle discrimination method for UWB signals to enhance localization accuracy.
- To develop a tightly integrated UWB/MEMS IMU positioning algorithm that accounts for dynamic NLOS characteristics.
- To improve the robustness of UWB positioning in environments with signal occlusion and multipath effects.
Main Methods:
- A dynamic NLOS angle discrimination technique based on horizontal angles was developed to identify and weight UWB ranging observations.
- A tightly integrated positioning algorithm combining UWB and MEMS IMU data was implemented, incorporating NLOS angle discrimination and map constraints.
- UWB signal occlusion characteristics were analyzed concerning horizontal angles to understand ranging error behavior.
Main Results:
- The proposed algorithm achieved low positioning errors: 0.189m (northward), 0.126m (eastward), and 0.243m (planar) in initial experiments.
- Further experiments yielded improved errors: 0.119m (northward), 0.134m (eastward), and 0.211m (planar).
- Positional accuracy in the plane showed significant improvements of 22.9% and 28.5% compared to the Robust Adaptive Kalman Filtering algorithm.
Conclusions:
- The dynamic NLOS angle discrimination method effectively mitigates UWB ranging errors in occluded environments.
- The integrated UWB/MEMS IMU algorithm demonstrates superior positioning performance compared to traditional methods, especially in challenging dynamic scenarios.
- The findings contribute to more reliable and accurate localization systems utilizing UWB technology in real-world applications.
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