基于数据融合的无人帆船真风计算方法

何成龙; 迟书凯; 宇文国朴; 胡新遥; 魏鹏飞; 黎明

doi:10.11993/j.issn.2096-3920.2023-0017

基于数据融合的无人帆船真风计算方法

doi: 10.11993/j.issn.2096-3920.2023-0017

中国海洋大学工程学院, 山东青岛, 266500

基金项目: 青岛市关键技术公关及产业化示范项目资助(22-3-3-hygg-7-hy)科技开发与协作项目资助(20210109)

详细信息

通讯作者:
迟书凯(1980-), 男, 博士, 高级工程师, 主要研究方向为海洋智能仪器

中图分类号: TJ630.1; U674.94
计量
- 文章访问数: 770
- HTML全文浏览量: 7
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2023-02-27
- 修回日期: 2023-04-04
- 录用日期: 2023-05-08
- 网络出版日期: 2024-03-08

Calculation Method of True Wind of Unmanned Sailboat Based on Data Fusion

Engineering College, Ocean University of China, Qingdao 266500, China

摘要

摘要: 针对无人帆船真风获取困难且所用风传感器受帆船姿态影响的问题, 提出了一种基于姿态信息、相对风和航行风融合的无人帆船真风计算方法。首先利用姿态仪获得帆船的俯仰角和横滚角, 通过空间坐标旋转变换矫正相对风测量结果; 其次利用卡尔曼滤波算法对航行风和矫正后的相对风进行滤波; 最后利用扩展卡尔曼滤波进行真风融合计算。实验证明, 该方法能够有效抑制帆船运动对风测量的影响, 准确提取真风风速和风向, 满足无人帆船航行控制需求。
- 无人帆船 /
- 真风 /
- 数据融合 /
- 卡尔曼滤波
Abstract: Since the unmanned sailboat is difficult to obtain the true wind, and the wind sensor used is affected by the attitude of the sailboat, a calculation method of the true wind of the unmanned sailboat based on the fusion of attitude information, relative wind, and sailing wind was proposed. Firstly, the pitch angle and roll angle of the sailboat were obtained by using the attitude instrument, and the relative wind measurement results were corrected by the spatial coordinate rotation and transformation. Secondly, the Kalman filter algorithm was used to filter the sailing wind and the corrected relative wind. Finally, the extended Kalman filter was utilized to perform true wind fusion calculations. Experiments have proved that this method can effectively suppress the influence of sailboat motion on wind measurement, accurately extract true wind speed and wind direction, and ensure the sailing control of unmanned sailboats.
- unmanned sailboat /
- true wind /
- data fusion /
- Kalman filter

HTML全文

图 1 速度三角形

Figure 1. Velocity triangle

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图 2 设计系统整体框图

Figure 2. Overall block diagram of the designed system

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图 3 空间坐标旋转

Figure 3. Space coordinate rotation

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图 4 第1组参数滤波效果

Figure 4. Filter effect of group 1 parameters

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图 5 第2组参数滤波效果

Figure 5. Filter effect of group 1 parameters

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图 6 参数选用判定流程图

Figure 6. Flow chart of parameter selection judgment

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图 7 参数自适应卡尔曼滤波效果

Figure 7. Effect of parameter adaptive Kalman filter

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图 8 实验平台

Figure 8. Experiment platform

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图 9 实验框图

Figure 9. Experiment block diagram

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图 10 俯仰角0°时不同横滚角风向风速矫正结果

Figure 10. Correction results of wind direction and speed for different roll angles with a pitch angle of 0°

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图 11 横滚角0°时不同俯仰角风向风速矫正结果

Figure 11. Correction results of wind direction and speed for different pitch angles with a roll angle of 0°

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图 12 真风融合结果

Figure 12. True wind fusion results

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图 13 真风融合结果误差

Figure 13. True wind fusion result error

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参考文献(17)

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