大方位失准角MIMU空中对准建模及半物理仿真  

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

作　　者：曹娟娟[1] 房建成[1] 盛蔚[1] 

机构地区：[1]北京航空航天大学仪器科学与光电工程学院,北京100083

出　　处：《北京航空航天大学学报》2008年第1期63-66,共4页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国防基础科研资助项目(D2120060013);新世纪人才资助项目(NCET-04-0162)

摘　　要：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%.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.

关 键 词：微惯性测量单元 全球定位系统 空中对准 自适应卡尔曼滤波 

分 类 号：V249.32[航空宇航科学与技术—飞行器设计]