联邦模糊自适应卡尔曼滤波在速度+姿态传递对准中的应用

在系统动态模型和噪声统计特性无法完全获得的情况下，通过调整卡尔曼滤波器的相关参数提高弹载子惯导对准性能，其效果是很有限的，采用联邦模糊自适应卡尔曼滤波方法进行速度＋姿态匹配传递对准，并对算法进行了可行性分析与仿真验证。仿真结果表明，在系统动态模型和噪声的统计特性不确定的情况下，速度+姿态匹配传递对准的联邦模糊自适应卡尔曼滤波短时间内能够较好地估计出弹载子惯导的初始姿态失准角，是一种非常有效的信息融合方法。

Velocity and Attitude Matching of Transfer Alignment by Using Federated Fuzzy Adaptive of Kalman Filter

It is limited to improve alignment performance of airborne slave inertial navigation system by adjusting the parameters of Kalman filter when the system dynamic model and the disturbances in measurements are completely unknown.The federated fuzzy adaptive of Kalman filter is adopted to design the transfer alignment (TA) scheme of velocity and attitude matching,meanwhile,there are feasible analysis and simulation of velocity and attitude matching.The simulation results show that the federated fuzzy adaptive of Kalman filter is a better method to estimate the initial attitude misalignment angle of airborne slave inertial navigation system in short time,when the system dynamic model and the disturbances in measurements are completely unknown.