基于四元素的扩展卡尔曼滤波航姿参考系统算法设计  

Design of Extended Kalman Filtering for AHRS Algorithm Based on Four Elements

作　　者：刘维亭[1] 白杨[1] 

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212003

出　　处：《船舶工程》2015年第4期53-56,共4页Ship Engineering

摘　　要：为了优化飞行姿态信息,设计一种适用于捷联式航姿参考系统的九态扩展卡尔曼滤波算法,得到最优估计。为了验证此EKF算法的可行性和滤波效果,采用AHRS300惯性测量单元的数据进行MATLAB滤波算法仿真,把感器采集数据平滑计算后,建立精确的MATLAB算法模型作为参考。把两种结果作差比较,计算姿态角误差。从仿真结果可以看出,所设计的算法能够获得较好的姿态角精度,证明此扩展卡尔曼滤波性能良好。In order to optimize the flight information, a suitable for Strapdown Attitude Heading Reference System for the nine state extended Kalman filtering algorithm is designed in this paper to get the best estimate suitable. In order to verify the feasibility of this EKF algorithm and filtering effect used the AHRS300 inertial measurement unit data for the MATLAB filtering algorithm simulation and the smooth computation sensor data to establish MATLAB attitude algorithm model as reference. The two solutions are compared to the results of difference of which, and draws the error table. The simulation results show that the designed EKF algorithm can achieve better precision, which has a good filtering petformance.

关 键 词：姿态解算 扩展卡尔曼滤波器 惯性传感器 

分 类 号：U666.12[交通运输工程—船舶及航道工程] TJ765[交通运输工程—船舶与海洋工程]