| 基于模糊Kalman滤波的港口车辆组合定位方法研究 |
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| 引用本文： | 杨勇生,迟景成,姚海庆.基于模糊Kalman滤波的港口车辆组合定位方法研究[J].全球定位系统,2020,45(6):80-85. |
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| 作者姓名： | 杨勇生 迟景成 姚海庆 |
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| 作者单位： | 上海海事大学物流科学与工程研究院,上海201306;上海海事大学物流科学与工程研究院,上海201306;上海海事大学物流科学与工程研究院,上海201306 |
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| 摘 要： | 针对北斗卫星导航系统（BDS）/惯性导航系统（INS）组合导航系统在遮挡环境下定位失效这一问题，通过分析组合导航系统中传感器的状态变化对定位精度的影响，设计了一种基于传感器工作状态的模糊逻辑推理系统，并与卡尔曼滤波算法相结合，通过实时调整系统量测噪声方差的方法提高定位精度.在港口环境下的无人车辆上进行了实验，实验表明，提出的方法能有效提高遮挡环境下无人车辆的定位精度，并具有良好的鲁棒性.
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| 关 键 词： | 系统工程 组合定位系统 模糊卡尔曼滤波 组合导航 BDS/INS |
| 收稿时间： | 2020-10-09 |
Research on port vehicle combined positioning method based on fuzzy Kalman filter |
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| Affiliation: | Instate of Logistics Science and Engineening ShangHai Maritime University, Shanghai 201306, China |
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| Abstract: | Aiming at the problems of BDS/INS integrated navigation system positioning failure in the obstructed environment, by analyzing the impact of sensor status changes in the integrated navigation system on positioning accuracy, we design a fuzzy logic inference system based on the status of the system, combined with the Kalman filter algorithm, the positioning accuracy is improved by real-time adjustment of the noise variance of the system measurement. Finally, experiments were carried out on unmanned vehicles in a port environment. Experiment shows that the proposed method can effectively improve the positioning accuracy of unmanned vehicles in an occluded environment, and has good robustness. |
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