惯性导航系统中的Kalman滤波技术

Kalman Filter Algorithms applied to INS

近年来针对在实际应用中出现的Kalman滤波精度低,甚至滤波器发散的问题,出现了多种改进的状态估计算法,研究了偏差分离滤波,自适应Kalman滤波,H∞滤波,鲁棒Kalman滤波,根据它们的特点,对于它们在惯性导航领域中的应用进行了论述和分析,这些算法对于提高Kalman滤波精度,增强滤波的稳定性,提高惯性导航系统性能具有一定的效果,同时具有广阔的应用前景。

In recent years,there has been a great deal of research of improved algorithm about state estimation aiming at the problem of kalman filter degradation and divergence when it used in practical applications.The bias-separated filter,adaptive kalman filter,H~∞ filter,robust kalman filter are reviewed.According to their features,it generalizes and analyzes theirs application to the inertial navigation system.The algorithms enhance the accuracy of Kalman filter,reinforce the stability of the filter and improve the performance of the inertial navigation system.