基于级联卡尔曼滤波的动基座MIMU初始对准方法  

Initial Alignment of Moving MIMU Based on Kalman Cascaded Filter

作　　者：侯梦婷 王雪梅 单斌 许哲 李灿 HOU Mengting;WANG Xuemei;SHAN Bin;XU Zhe;LI Can(Rocket Force University of Engineering,Xi'an 710000,China)

机构地区：[1]火箭军工程大学,西安710000

出　　处：《电光与控制》2023年第11期113-119,共7页Electronics Optics & Control

摘　　要：为了实现低成本微惯性测量单元(MIMU)的自对准功能、提高自对准精度,提出了一种基于级联卡尔曼滤波(KCF)的动基座GPS单天线辅助MIMU自对准方法。首先,对GPS单天线测得的速度矢量随机误差进行了总平均经验模态分解(MEEMD),信号重构后使用卡尔曼滤波对其降噪解算得到航向角测量;其次,以基座姿态角和陀螺常值漂移为状态量建立了系统的状态方程,并融合加速度计和GPS单天线测量信息,建立了系统的观测方程;然后,使用自适应无迹卡尔曼滤波进行信息融合,实现了基座姿态角的最优估计。经仿真验证对比,所提算法有效提高了自对准精度。仿真结果验证了所提算法在GPS单天线辅助MIMU自对准中的优越性。In order to realize the self-alignment function of the low-cost Micro Inertial Measurement Unit(MIMU)and improve the self-alignment accuracy,this paper proposes a method of moving MIMU self-alignment assisted by GPS single antenna based on Kalman Cascade Filtering(KCF).Firstly,the Modified Ensemble Empirical Mode Decomposition(MEEMD)is performed on the random error of the velocity vector measured by the GPS single antenna,and after signal reconstruction,Kalman filtering is used for denoising calculation to obtain the heading angle measurement.Secondly,the state equation of the system is established by taking the attitude angles of the base and gyroscope constant drift as the state variables,and the observation equation of the system is established by fusing the accelerometer and GPS single antenna measurement information.Then,the Adaptive Unscented Kalman Filter(AUKF)is used for information fusion,and the optimal estimation of the attitude angles of the base is realized.After simulation verification and comparison,it is proved that the proposed method effectively improves the self-alignment accuracy.The simulation results validate the superiority of the proposed algorithm in MIMU self-alignment assisted by GPS single antenna.

关 键 词：微惯性测量单元 初始对准 总平均经验模态分解 自适应级联卡尔曼滤波 

分 类 号：TP211.6[自动化与计算机技术—检测技术与自动化装置]