| Xu Dongfu (徐东甫),Pei Xinbiao,Bai Yue,Peng Cheng,Wu Ziyi,Xu Zhijun.[J].高技术通讯(英文),2017,23(2):165~172 |
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| Altitude information fusion method and experiment for UAV |
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| DOI：10.3772/j.issn.1006-6748.2017.02.007 |
| 中文关键词: |
| 英文关键词: unmanned aerial vehicles (UAV), altitude information fusion, multi-sensor, adaptive Kalman filter |
| 基金项目: |
| Author Name | Affiliation | | Xu Dongfu (徐东甫) | | | Pei Xinbiao | | | Bai Yue | | | Peng Cheng | | | Wu Ziyi | | | Xu Zhijun | |
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| 中文摘要: |
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| 英文摘要: |
| Altitude regulation is a fundamental problem in UAV (unmanned aerial vehicles) control to ensure hovering and autonomous navigation performance. However, data from altitude sensors may be unstable by interference. A digital-filter-based improved adaptive Kalman method is proposed to improve accuracy and reliability of the altitude measurement information.A unique sensor data fusion structure is designed to make different sensors switch automatically in different environment. Simulation and experimental results show that an improved Sage-Husa adaptive extended Kalman filter (SHAEKF) is adopted in altitude data fusion which means that altitude error is limited to 1.5m in high altitude and 1.2m near the ground. This method is proved feasible and effective through hovering flight test and three-dimensional track flight experiment. |
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