一种鲁棒自适应推广Kalman滤波及其在飞行状态估计中的应用

本文在自适应推广Kalman滤波基础上，为了防止滤波发散，改善自适应Kalman滤波的数值稳定性和计算效率，利用U－D分解滤波，并引进滤波发散的判据等，提出一种鲁棒自适应推广Kalman滤波新算法，并把该算法应用于飞行器飞行状态估计问题，仿真及实际计算结果证明了本文方法的有效性。

A ROBUST ADAPTIVE EXTENDED KALMAN FILTER AND ITS APPLICATION TO FLIGHT STATE ESTIMATION

In order to improve the numerical stability and computation efficiency and prevent the divergence of adaptive Ks]man fillter, a new robust adaptive extended Kalman filter based on U-D covariance fsctorization is proposed in this paper. The new algorithm is used in the flight state estimation of aircraft. The results of simulated and real flight test data computation show that the new algorithm proposed can provide more precise estimation than the extended Kalman filter in solring flight state estimation problem corrupted by timevariant noise. Moreover, the new algorithm requires less noise statistics information, and has better convergency than the adaptive extended Kalman filter. When the adaptive extended Kalman filter diverges, the new algorithm can also give good estimation results.