基于改进联邦Kalman滤波的组合校准方法研究

联邦滤波器广泛应用于多传感器信息融合领域,联邦滤波中的信息分配原则影响滤波精度.针对联邦Kalman滤波器进行改进,采用基于估计协方差阵奇异值动态确定信息分配系数.对子滤波器进行重置时,采用新的重置方法,保证了子滤波器误差协方差阵的对称性,确保Kalman滤波器的一致收敛稳定性.新的联邦滤波算法允许每个状态分量拥有不同的动态信息分配因子,从而改进了联邦滤波信息融合的精度.设计了SINS/GPS/电子罗盘组合导航系统,仿真结果说明,与传统联邦滤波算法相比,改进的联邦滤波器估计精度得到了提高,可以更好地对SINS误差进行校准,提高系统的精度.

Research on Integrated Calibration Based on Improved Federated Kalman Filter

Federated filter has been widely used in the field of multi-sensor information fusion, and information distribution rule can directly affect the filtering accuracy. In this article, federated Kalman filter is improved by determining the information-distributing coefficients dynamically for federated filter with resetting configuration based on singular value of the covariance matrix of the estimated errors. The sub-filter is reset with new methods to ensure the symmetry of the sub-filters'' error covariance matrix and the stability of the Kalman filter''s uniform convergence. The new algorithm allows each system state variable to have different information distribution factors, and hence improves the estimation accuracy of the federated filter. An INS/GPS/electrical compass integrated navigation system is designed by using federated Kalman filter technique. The simulation shows that compared with the traditional method, the new federated Kalman filter can improve the precision of the estimated errors and enable better error-correction and accuracy of SINS