| 修正扩维无迹卡尔曼滤波算法研究 |
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| 引用本文： | 任晓斌,聂桂根,李连艳,陈祖岸,雷浩川.修正扩维无迹卡尔曼滤波算法研究[J].测绘通报,2019,0(5):83-87,101. |
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| 作者姓名： | 任晓斌 聂桂根 李连艳 陈祖岸 雷浩川 |
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| 作者单位： | 武汉大学卫星导航定位技术研究中心,湖北 武汉,430079;武汉大学土木建筑工程学院,湖北 武汉,430079;恩施州城乡规划管理局,湖北 巴东,444300;青海大学地质工程系,青海 西宁,810016 |
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| 摘 要： | 在脉冲星导航中,角位置误差是主要的误差源之一。因此本文基于X射线脉冲星导航,提出了一种修正扩维无迹卡尔曼滤波(MASUKF)算法进行角位置误差的改进。MASUKF算法在原扩维无迹卡尔曼滤波(ASUKF)算法的基础上加入了Roamer延迟的高阶项,并将其作为误差项,将修改后的误差项代入状态方程与量测方程中,即可进行仿真分析。在仿真中,首先将ASUKF算法与UKF算法进行对比仿真模拟试验,结果显示ASUKF算法能显著地提高约45 m的定位精度,在X、Y、Z 3方向的速度误差估计精度约提高了20%;然后比较ASUKF与MASUKF算法,结果显示MASUKF算法较ASUKF算法的速度误差与位置误差的估计精度均提高2%以上。
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| 关 键 词： | 无迹卡尔曼滤波 扩维无迹卡尔曼滤波 修正扩维无迹卡尔曼滤波 X射线脉冲星导航 误差项 |
| 收稿时间： | 2018-10-08 |
Research on the algorithm of modified augmented state unscented Kalman filter |
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| REN Xiaobin,NIE Guigen,LI Lianyan,CHEN Zuan,LEI Haochuan.Research on the algorithm of modified augmented state unscented Kalman filter[J].Bulletin of Surveying and Mapping,2019,0(5):83-87,101. |
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| Authors: | REN Xiaobin NIE Guigen LI Lianyan CHEN Zuan LEI Haochuan |
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| Institution: | 1. GNSS Research Center, Wuhan University, Wuhan 430079, China;
2. School of Civil Engineering, Wuhan University, Wuhan 430079, China;
3. Urban and Rural Planning Bureau, Badong 444300, China;
4. Geological Engineering Department, Qinghai University, Xining 810016, China |
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| Abstract: | In pulsar navigation, angular position error is one of the main sources of error. Therefore, based on X-ray pulsar navigation, MASUKF filtering algorithm is proposed to improve the angular position error. Based on the original ASUKF algorithm, the MASUKF algorithm adds the high-order term of the Roamer delay as an error term, and substitutes the modified error term into the state equation and measurement. In the equation, simulation analysis can be performed. In the simulation, the ASUKF algorithm is first compared with the UKF algorithm for simulation experiments. The results show that the ASUKF algorithm can significantly improve the positioning accuracy of about 45 m, and the speed error in the X, Y, and Z directions. The estimation accuracy is improved by about 20%. Then, the ASUKF and MASUKF algorithms are compared. The results show that the velocity accuracy and position error estimation accuracy of the MASUKF algorithm are more than 2% higher than the ASUKF algorithm. |
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| Keywords: | UKF ASUKF MASUKF X-ray pulsar-based navigation error term |
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