MEMSIMU/GNSS联邦卡尔曼滤波中的基于四元数的约束算法(英文)

Quaternion based constrained algorithm in federated Kalman filtering for MEMS IMU/GNSS

当全球导航卫星系统(GNSS)失效时,微硅机械(MEMS)惯性测量单元(IMU)与GNSS组合而成的导航系统性能会下降。针对于陆地车辆的导航应用,建立了一个联邦卡尔曼滤波器,四元数是其中一个局部滤波器的部分待估计状态。四元数所得到推算的沿车辆机体坐标系的加速度约束扩展了滤波器的观测量。车载试验表明,与传统滤波算法相比,使用该算法可使三维位置导航精度在GNSS信号失效30 s时提高25%,姿态和速度精度也相应的提高。

The performance of MEMS IMU/GNSS integrated system would degrade with outages of GNSS signal. For land vehicle applications, a federated Kalman filter was established. The quaternion was employed as part of states in one of the local filters. The acceleration constraint derived from quaternion was applied along the vehicle’s body frame to expand observables in the filter. The field test shows that, compared with conventional filtering algorithms, the proposed algorithm brings 25% performance improvement in three-dimension（3D） positioning during 30 s GNSS outages. The accuracy of attitude and velocity is improved as well.