[1]张大龙,余 刚,李致远,等.考虑杆臂误差的组合导航分离协方差交叉算法[J].郑州大学学报(工学版),2022,43(03):8-14.
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考虑杆臂误差的组合导航分离协方差交叉算法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
43
期数:
2022年03期
页码:
8-14
栏目:
出版日期:
2022-04-10

文章信息/Info

Title:
Split Covariance Intersection Algorithm for Integrated Navigation
System Considering Lever Arm Error
作者:
张大龙余 刚李致远韩刚涛
文献标志码:
A
摘要:
针对传统北斗/ 惯导组合导航系统进行信息融合时未考虑估计源之间的相关性而不能保证融
合一致性的问题,提出一种分离协方差交叉滤波( split CIF) 组合导航信息融合算法。将误差协方差矩阵
分离为相关部分和独立部分分别进行处理,实时更新最优滤波增益并通过量测信息获得一致性融合估
计,改善了融合相关数据时造成滤波过度收敛的问题。此外,在高精度组合导航中,杆臂误差是一个重
要误差源, 组合导航时会造成导航定位精度严重下降,通过静态杆臂测量并对惯导更新信息进行杆臂
误差补偿的方法降低杆臂效应影响,进一步提升导航定位精度。仿真结果表明:东向速度误差最大为
0. 041 m/ s,纬度误差最大为0. 495 m与补偿后的卡尔曼滤波相比,精度分别提高了45. 8%和34. 0%与
扩展卡尔曼滤波相比,精度分别提高了55. 1%和10. 0%。考虑杆臂误差补偿的split CIF 算法对杆臂估
计具有较好的准确性且具有较高的导航精度。
Abstract:
In the information fusion procedures of the traditional Beidou/ INS integrated navigation systems,
the correlation between the estimated sources was not considered, which could not guarantee the consistency of
information fusion, a split covariance intersection filter (split CIF)-based information fusion algorithm was
proposed. The algorithm separated the error covariance matrix into correlated part and independent part for
processing, respectively. Consistent fusion estimation was obtained by measuring information and optimal filter
gain updated in real time, which overcame the problem of the filter over-convergence caused by the fusion correlation
data. in addition, in high precision integrated navigation, the lever arm error is an important error
source. The accuracy of navigation positioning results could decrease severely for Beidou/ INS integrated navigation
systems. In this paper, the method of static lever arm measurement and error compensation for INS
update information was used to reduce the influence of lever arm effect and further to improve the positioning
accuracy. The simulation results showed that split CIF considering lever arm error compensation had good
accuracy for lever arm estimation and high navigation accuracy. The maximum error accuracy of east velocity
was 0. 041 m / s, and the maximum accuracy of latitude error was 0. 495 m. Compared with the compensated
Kalman filter, it increased by 45. 8% and 34. 0%, and compared with EKF, the error accuracy increased by
55. 1% and 10. 0%, respectively.
更新日期/Last Update: 2022-04-29