| 基于MEMS-INS/GNSS组合导航抗差自适应Kalman滤波算法 |
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| 引用本文： | 周彬,赵万良,荣义杰,胡小毛,马吉雨.基于MEMS-INS/GNSS组合导航抗差自适应Kalman滤波算法[J].导航与控制,2018,17(4):14-20. |
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| 作者姓名： | 周彬 赵万良 荣义杰 胡小毛 马吉雨 |
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| 作者单位： | 上海航天控制技术研究所，上海 201109；上海惯性工程技术研究中心，上海 201109,上海航天控制技术研究所，上海 201109；上海惯性工程技术研究中心，上海 201109,上海航天控制技术研究所，上海 201109；上海惯性工程技术研究中心，上海 201109,上海航天控制技术研究所，上海 201109；上海惯性工程技术研究中心，上海 201109,上海航天控制技术研究所，上海 201109；上海惯性工程技术研究中心，上海 201109 |
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| 摘 要： | 标准的Kalman滤波器在组合导航领域得到了广泛的应用，然而在实际运动过程中，载体的运动模型是复杂多变的，无法准确掌握系统的动态特性。针对高动态环境下载体动态复杂多变特性带来的动力学模型难以精确构建问题，以及卫星跟踪环路信号易受扰动导致的观测信息出现异常粗差问题，设计了一种基于MEMS-INS/GNSS组合导航系统抗差自适应Kalman滤波算法，研究了优化自适应因子的求解方法。通过跑车试验证明了该算法能够有效地抑制误差发散，提供更加精确的导航定位结果，更好地控制观测信息误差以及动力学模型异常所带来的影响。
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| 关 键 词： | 抗差自适应滤波 Kalman滤波 MEMS INS/GNSS组合导航 自适应因子 抗差估计 |
Robust Adaptive Kalman Filtering Algorithm for Integrated Navigation Based on MEMS-INS/GNSS |
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| ZHOU Bin,ZHAO Wan-liang,RONG Yi-jie,HU Xiao-mao and MA Ji-yu.Robust Adaptive Kalman Filtering Algorithm for Integrated Navigation Based on MEMS-INS/GNSS[J].Navigation and Control,2018,17(4):14-20. |
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| Authors: | ZHOU Bin ZHAO Wan-liang RONG Yi-jie HU Xiao-mao and MA Ji-yu |
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| Institution: | Shanghai Institute of Spaceflight Control Technology, Shanghai 201109; Shanghai Engineer Research Center of Inertia, Shanghai 201109,Shanghai Institute of Spaceflight Control Technology, Shanghai 201109; Shanghai Engineer Research Center of Inertia, Shanghai 201109,Shanghai Institute of Spaceflight Control Technology, Shanghai 201109; Shanghai Engineer Research Center of Inertia, Shanghai 201109,Shanghai Institute of Spaceflight Control Technology, Shanghai 201109; Shanghai Engineer Research Center of Inertia, Shanghai 201109 and Shanghai Institute of Spaceflight Control Technology, Shanghai 201109; Shanghai Engineer Research Center of Inertia, Shanghai 201109 |
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| Abstract: | The standard Kalman filter has been widely used in the field of integrated navigation. However, in the actual process of motion, the motion model of the carrier is complex and changeable, and the dynamic characteristics of the system can not be accurately mastered. In the case of high dynamic environment, the dynamic model caused by the dynamic and complex characteristics of the downloading body is difficult to be constructed accurately, and the abnormal information of the observation information caused by the disturbance of the satellite tracking loop signals is abnormal. In this paper, a robust adaptive Kalman filtering algorithm for integrated navigation system based on MEMS/GNSS is designed. The experiment shows that the algorithm can effectively suppress the error divergence, provide , more and the influence of the anomaly of the dynamic model. |
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| Keywords: | robust adaptive filtering Kalman filtering MEMS-INS/GNSS integrated navigation adaptive factor robust estimation |
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