A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonl...A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.展开更多
针对重力扰动引起惯性水平基准姿态测量误差进而导致天文/惯性组合导航系统定位精度下降的问题,提出天文/惯性组合系统中的重力扰动补偿方法。首先,基于导航误差模型分析了影响天文/惯性组合导航系统定位精度的主要因素。其次,推导了重...针对重力扰动引起惯性水平基准姿态测量误差进而导致天文/惯性组合导航系统定位精度下降的问题,提出天文/惯性组合系统中的重力扰动补偿方法。首先,基于导航误差模型分析了影响天文/惯性组合导航系统定位精度的主要因素。其次,推导了重力扰动、惯性水平基准姿态测量误差与天文导航定位误差之间的传播机理。然后,研究了重力扰动建模与修正方法,并将重力扰动补偿方法应用于惯性水平基准的导航解算回路中,实现重力扰动的有效补偿。跑车试验结果表明,所提重力扰动补偿方法可以将天文/惯性组合导航系统中定位误差的振荡幅值由1.6 n mile降低至0.5 n mile。展开更多
基金supported by the National Natural Science Foundation of China (60535010)
文摘A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.
文摘针对重力扰动引起惯性水平基准姿态测量误差进而导致天文/惯性组合导航系统定位精度下降的问题,提出天文/惯性组合系统中的重力扰动补偿方法。首先,基于导航误差模型分析了影响天文/惯性组合导航系统定位精度的主要因素。其次,推导了重力扰动、惯性水平基准姿态测量误差与天文导航定位误差之间的传播机理。然后,研究了重力扰动建模与修正方法,并将重力扰动补偿方法应用于惯性水平基准的导航解算回路中,实现重力扰动的有效补偿。跑车试验结果表明,所提重力扰动补偿方法可以将天文/惯性组合导航系统中定位误差的振荡幅值由1.6 n mile降低至0.5 n mile。
