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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.12726 |
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| _version_ | 1866916653883719680 |
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| author | Zhang, Fengyun Li, Jia Zhang, Xiaoqing Duan, Shukai Yang, Shuang-Hua |
| author_facet | Zhang, Fengyun Li, Jia Zhang, Xiaoqing Duan, Shukai Yang, Shuang-Hua |
| contents | This paper presents a high-precision positioning system that integrates ultra-wideband (UWB) time difference of arrival (TDoA) measurements, inertial measurement unit (IMU) data, and ultrasonic sensors through factor graph optimization. To overcome the shortcomings of standalone UWB systems in non-line-of-sight (NLOS) scenarios and the inherent drift associated with inertial navigation, we developed a novel hybrid fusion framework. First, a dynamic covariance estimation mechanism is incorporated, which automatically adjusts measurement weights based on real-time channel conditions. Then, a tightly-coupled sensor fusion architecture is employed, utilizing IMU pre-integration theory for temporal synchronization. Finally, a sliding-window factor graph optimization backend is utilized, incorporating NLOS mitigation constraints. Experimental results in complex indoor environments show a 38\% improvement in positioning accuracy compared to conventional Kalman filter-based approaches, achieving a 12.3 cm root mean square (RMS) error under dynamic motion conditions. The system maintains robust performance even with intermittent UWB signal availability, down to a 40\% packet reception rate, effectively suppressing IMU drift through multi-modal constraint fusion. This work offers a practical solution for applications that require reliable indoor positioning in GPS-denied environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12726 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Indoor Fusion Positioning Based on "IMU-Ultrasonic-UWB" and Factor Graph Optimization Method Zhang, Fengyun Li, Jia Zhang, Xiaoqing Duan, Shukai Yang, Shuang-Hua Systems and Control This paper presents a high-precision positioning system that integrates ultra-wideband (UWB) time difference of arrival (TDoA) measurements, inertial measurement unit (IMU) data, and ultrasonic sensors through factor graph optimization. To overcome the shortcomings of standalone UWB systems in non-line-of-sight (NLOS) scenarios and the inherent drift associated with inertial navigation, we developed a novel hybrid fusion framework. First, a dynamic covariance estimation mechanism is incorporated, which automatically adjusts measurement weights based on real-time channel conditions. Then, a tightly-coupled sensor fusion architecture is employed, utilizing IMU pre-integration theory for temporal synchronization. Finally, a sliding-window factor graph optimization backend is utilized, incorporating NLOS mitigation constraints. Experimental results in complex indoor environments show a 38\% improvement in positioning accuracy compared to conventional Kalman filter-based approaches, achieving a 12.3 cm root mean square (RMS) error under dynamic motion conditions. The system maintains robust performance even with intermittent UWB signal availability, down to a 40\% packet reception rate, effectively suppressing IMU drift through multi-modal constraint fusion. This work offers a practical solution for applications that require reliable indoor positioning in GPS-denied environments. |
| title | Indoor Fusion Positioning Based on "IMU-Ultrasonic-UWB" and Factor Graph Optimization Method |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2503.12726 |