卡尔曼滤波在无陀螺捷联惯导系统中的应用

Gyroscope-free Strapdown Inertial Navigation System Using Kalman Filtering

无陀螺捷联惯导系统仅利用加速度计就可以完成惯性测量与导航任务,应用前景广阔,然而角速度解算精度不高一直是其难以实现工程化的瓶颈问题。本文基于一种9加速度计配置方案,设计了一种削弱三轴耦合的卡尔曼滤波器,将仿真结果与其他角速度解算方法进行了比较,实验表明,该滤波法具有较高的解算精度。

Gyroscope-free strapdown inertial navigation system （ GFSINS ） can play the role of inertial measurement and navigation only using accelerometer, which owns wide application foreground. However, the low precision of calculating angular-velocity is always the bottleneck problem of application in reality. Based on a nine accelerometers allocation scheme, an H∞ robust filter is designed to improve the calculation precision. Then by use of certain missile trajectory data, the simulation results of four calculating methods （integral, extraction, standard Kalman filter and H∞ robust filter） are given out under the condition of white noise and colored noise respectively. After comparing all the simulation results, we can find that the H∞ robust filter has a higher calculation precision and better robustness.