一种基于AKF的MEMS惯性导航系统姿态初始化方法  

An Attitude Initialization Method for MEMS Inertial Navigation System Based on AKF

作　　者：陈光武[1,2] 李文元 程鉴皓 张琳婧 CHEN Guang-wu;LI Wen-yuan;CHENG Jian-hao;ZHANG Lin-jing(Automatic Control Research Institute,Lanzhou Jiaotong University Lanzhou 730070,China;Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province,Lanzhou Jiaotong University Lanzhou 730070,China)

机构地区：[1]兰州交通大学自动控制研究所,甘肃兰州730070 [2]兰州交通大学甘肃省高原交通信息工程及控制重点实验室,甘肃兰州730070

出　　处：《控制工程》2021年第12期2402-2409,共8页Control Engineering of China

基　　金：国家自然科学基金资助项目(61863024);甘肃省基础研究创新群体计划项目(1606RJIA327);甘肃省高等学校科研项目(2018C-11);甘肃省自然科学基金资助项目(18JR3RA107);甘肃省科技计划项目(18CX3ZA004)。

摘　　要：为了实现微机电系统(micro-electro-mechanical system,MEMS)惯性导航系统的初始对准,即姿态初始化,提出一种基于加速度计与磁强计的姿态初始化方法。首先,推导了该方法计算姿态角的公式,对该方法计算的姿态角进行误差分析。然后,为提高对准精度,对惯性导航系统建立模型,将自适应卡尔曼滤波(adaptive Kalman filter,AKF)算法引入对准过程,在线实时估计量测噪声。最后,在双轴实验转台与MEMS实验板卡上开展实验。实验结果表明,使用所提方法不仅能够获得更高的对准精度,而且可以使系统的抗干扰能力得到提高。这为后续系统进行姿态解算与惯性导航提供了有力支撑。In order to realize the initial alignment of inertial navigation system of micro-electro-mechanical system(MEMS),namely attitude initialization,an attitude initialization method based on accelerometer and magnetometer is proposed in this paper.Firstly,the formula of attitude angle calculated by this method is deduced,and the error of attitude angle calculated by this method is analyzed.Then,in order to improve the alignment accuracy,the model of the inertial navigation system is established,and the adaptive Kalman filter(AKF)algorithm is introduced into the alignment process to estimate the measurement noise online and in real time.Finally,experiments are carried out on the two-axis experimental turntable and MEMS experimental computer card.The experimental results show that the proposed method can not only achieve higher alignment accuracy,but also improve the anti-jamming ability of the system,which provides a strong support for attitude calculation and inertial navigation of the follow-up system.

关 键 词：MEMS惯性导航系统 姿态初始化 失准角建模 自适应卡尔曼滤波算法 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]