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工学博士学位论文
目前，扩展卡尔曼滤波是研究初始对准和惯性/GPS组合导航问题的一个主要手段。
但初始对准和惯性/GPS组合导航问题本质上是非线性的，对模型进行线性化的扩展卡
尔曼滤波在一定程度上影响了系统的性能。近年来，直接使用非线性模型的
UKF(Unscented Kalman Filtering, UKF)和粒子滤波，正在逐渐成为研究非线性估计问题
的热点和有效方法。
本文研究了UKF和粒子滤波两种非线性滤波方法，并将其应用于非线性静基座对
准和惯性/GPS组合导航，系统地研究了初始对准和惯性/GPS组合导航中各种非线性项-Engineering PhD thesis Currently, EKF is the initial alignment study and inertial/GPS navigation of a major means. However, initial alignment and inertial/GPS navigation on the nature of the problem is nonlinear. on the model of linear expansion of the Kalman filter certain extent affected the performance of the system. In recent years, direct use of the non-linear model (UKF Unscented Kalman Filtering. UKF) and the particle filter, is gradually becoming nonlinear estimation of the hot and effective method. This paper studies the UKF and particle filter both nonlinear filtering method, will be applied to nonlinear static Base Alignment and inertial/GPS navigation, systematic study of initial alignment a
