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???????EKF??INS/GNSS???????????о?
引用本文:苗岳旺,孙付平,李飞,景晓鹏.???????EKF??INS/GNSS???????????о?[J].大地测量与地球动力学,2013,33(3):97-101.
作者姓名:苗岳旺  孙付平  李飞  景晓鹏
作者单位:1. 信息工程大学测绘学院,郑州,450052
2. 解放军72946部队,淄博,255000
3. 解放军96251部队,洛阳,471000
摘    要:???INS/GNSS????????GNSS????????????????о?????????EKF???????????????????INS?????????????μ???????INS/GNSS?????????????????????????????С?????????????????С????в??????????????Э???????????????????????????????????????????????????????????????GNSS?????д???????????????EKF??????????????????????????????????????????????????

关 键 词:INS/GNSS?????  ????EKF  ??????  ???Э????  ???????????  

RESEARCH ON APPLICATION OF TIGHTLY COUPLED INS/GNSS BASED ON ROBUST EXTENDED KALMAN FILTER
Miao Yuewang,Sun Fuping,Li Fei,and Jing Xiaopeng.RESEARCH ON APPLICATION OF TIGHTLY COUPLED INS/GNSS BASED ON ROBUST EXTENDED KALMAN FILTER[J].Journal of Geodesy and Geodynamics,2013,33(3):97-101.
Authors:Miao Yuewang  Sun Fuping  Li Fei  and Jing Xiaopeng
Institution:1) Institute of Surveying and Mapping,Information Engineering University,Zhengzhou 4500522) 72946 Troops of PLA,Zibo 2550003) 96251 Troops of PLA,Luoyang 471000
Abstract:Tightly coupled INS/GNSS based on Robust Extended Kalman Filter algorithm is researched aiming at the observation outliers of GNSS in the INS/GNSS integrated navigation. Firstly, the INS error equations resolved into the Local Lever Frame as well as the INS/GNSS tightly coupled measurement equations are given. Secondly, the resolved model based on least??square algorithm is constructed according to the measurement equations and the equal weight covariance is constructed by the least square residual statistic, then calculation steps are given. Finally, measured data are processed to verify the algorithm. Results show that: when the outliers exist in GNSS observations, the tightly coupled INS/GNSS integration based on Robust Extended Kalman Filter can weaken the impact of the observation outliers effectively, and can improve the precision of integrated navigation system.
Keywords:INS/GNSS tightly coupled  Robust Extended Kalman Filter  relative equivalent weight  equivalent covariance  variance inflation model
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