一种迭代的GPS/INS组合导航滤波算法

An Iterated Filtering for GPS/INS Integrated Navigation System

简要介绍了GPS/INS松组合导航系统状态方程和观测方程。针对标准Kalman滤波算法存在的状态方程截断误差、噪声统计特性的不确定性以及状态扰动异常的影响,给出了一种应用于GPS/INS组合导航系统的迭代滤波算法。该算法采用迭代策略,不断利用观测信息实时修正状态预报值。实测数据计算结果表明,通过对状态预报值的实时修正,该算法能够很好地抑制状态预报信息的不确定性和扰动异常等对导航解的影响。其滤波解精度明显优于标准Kalman滤波。

The observational and kinematic models of GPS/INS loosely integrated navigation system are introduced. In order to control the errors of ignoring high orders of kinematic models linearization, the uncertainness of systemic noises and the influences of the vehicle disturbances in movements, an iterated Kalman filtering（IKF） for GPS/INS integrated navigation system is established. It is shown, by comparison and analysis, that the IKF gives more actual and reliable parameter estimates of the maneuvering vehicles, the results derived by the IKF are better than those derived by standard Kalman filtering.