大方位失准角MIMU空中对准建模及半物理仿真

由于快速性的要求,微小型无人机不经过地面精确初始对准就升空作业,因此MIMU(Micro Inertial Measurement Unit)空中对准在大失准角下进行. 为了提高微小型无人机空中的反应速度和作业精度,把非线性误差部分作为状态变量,建立MIMU在大方位失准角下无需小角度近似的空中对准的线性模型,同时为解决噪声不确定导致滤波器发散的问题,提出将AKF (Adaptive Kalman Filter)应用在GPS(Global Positioning System)辅助MIMU的空中对准中,半物理仿真结果证实其取得了比基于非线性误差模型的EKF(Extended Kalman Filter)精度高且速度快的结果,不仅使MIMU的方位失准角由60° 快速下降到2° 左右,且所需时间仅为EKF的67%. 

Modeling and semi-physical simulation of in-flight alignment for MIMU under large heading error

The micro inertial measurement unit (MIMU) in micro unpiloted aerial vehicles initial alignment time is short, so in-flight alignment for MIMU is worked under large heading error with the global positioning system (GPS) assistant. Aimed at the requirement of high estimation precision and real time,a linear model with large heading error is introduced by regarding nonlinear vector as state vector, and adaptive Kalman filter (AKF) base on this linear model is used for MIMU in-flight alignment. The semi-physical simulation results show that this method has better precision than extended Kalman filter (EKF) with nonlinear model, and the heading error descends very quickly from 60° to around 2°. Furthermore, AKF need less computation time than EKF, only 67% of EKF.