GPS/IMU Integrated Navigation System Case Study with Unscented Kalman Filtering

被引:0
|
作者
Guo, Hang [1 ]
Wang, Lixun [1 ]
Yu, Min [2 ]
机构
[1] Nanchang Univ, Jiangxi 330031, Peoples R China
[2] Jiangxi Normal Univ, Dept Comp Sci, Digital Signal Proc, Nanchang, Jiangxi, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Unscented Kalman Filtering (UKF), which is a new nonlinear filtering method, avoids the linearization for nonlinear system state equations. Compared with the extended Kalman Filtering (EKF), the UKF has the characteristics of overcoming calculation divergence (such as linearization error), easy realization and higher state estimation accuracy as well. In the case study, the UKF is applied to an airplane GPS/IMU integrated navigation system including NovAtel, Trimble GPS receivers for the base station and rover, Litton LN 200 IMU on the aircraft. Differential GPS processing results are used for the observation values of the integrated system, the initial values of the airplane positions, velocities, and attitudes are approximately determined by GPS positions and velocities, and a modified observation equation has been developed. The field GPS/IMU data sets was collected in Alps mountain area flight test, 1999. The UKF, EKF, and IEKF position, velocity, and attitude parameters were obtained. The processing results showed that UKF has effectively solved nonlinearity problem of system state equation in this case study. And the UKF has position accuracy RMS of 0.018, 0.025, 0.041 meters in East, North, and Up directions, velocity accuracy RMS of 0.004, 0.005, 0.006 m/s in East, North, and Up directions, attitude error angle of 1.5, 15, 14 arcseconds in East, North, and Up directions, while EKF has position accuracy RMS of 0.018, 0.025, 0.041 meters in East, North, and Up directions, velocity accuracy RMS of 0.013, 0.017, 0.027 m/s in East, North, and Up directions, attitude error angle of 60, 61, 74 arcseconds in East, North, and Up directions,. Comparing with EKF, GPS/IMU integrated navigation parameters predicted by UKF have higher accuracy. In addition, EKF has experienced an attitude divergence for a time period of 450 seconds due to its linearization problem, but UKF with the modified observation equation didn't. It's also verified that the UKF is superior to the EKF.
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页码:698 / 705
页数:8
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