一种快速跟踪的卡尔曼滤波算法及其在舰船组合导航中的应用

在用卡尔曼滤波算法估计动态系统的状态时,如果系统运动状态发生突变,会导致滤波估值不能及时跟踪系统真实状态的变化。本从算法上分析了产生这种现象的原因,提出了根据不同传感器观测值的误差特点对算法进行改进的方法,使得卡尔曼滤波器跟踪速度和滤波精度大大提高,并将其成功地应用于推算船位/GPS组合导航系统。

A Kind of Kalman Filter Algorithm for Fast Tracking and its Application in Ship's Integrated Navigation Systems

When Kalma filtering algorithm is used to estimate the state of a dynamic system,it often results in that the estimated state can't follow the real state in time if the state of the system is undergoing a sudden change.In this paper,the reason of the problem is discussed by analyzing the algorithm and an improved method is proposed which utilizes the different error features of different sensors.This method can speed up the process of tracking and improve the precision of filtering and it is successfully applied to the reckoning/GPS integriated navigation system.