组合导航系统中一种基于特征值分解的自适应信息融合滤波算法

 基于分散滤波理论的联合滤波算法,可以有效地降低组合导航系统的计算负担,并且增强系统的容错性能。给出了一种联合滤波算法中信息分配系数的自适应计算方法,能够使联合系统根据导航过程中各传感器的信息质量的变化合理地反馈全局信息。仿真结果表明,该算法可以有效地降低由于导航子系统降级带来的滤波误差。

EIGENVALUE-DECOMPOSITION-BASED ADAPTIVE INFORMATION FUSION FILTER ALGORITHM FOR INTEGRATED NAVIGATION SYSTEMS

An efficient, adaptive federated Kalman filter is developed which can be applied to integrated navigation systems. Researchers have indicated that the information sharing scheme can influence the performance of the decentralized navigation filter. The estimation precision of local filters is directly reflected from the corresponding covariance matrix. So the aim is to calculate the information sharing coefficients on line through the variation of the covariance matrix. Based on a new adaptive algorithm, the information sharing coefficients of the local filters are decided in a federated structure, according to the change of the estimation quality in the local filters. The global information thus can be feasibly allocated and reset the estimation in local filters after information fusion stage. A practical federated filter example is given. Simulation results demonstrate that the adaptive INS/GPS/Doppler system can realize accurate real time navigation task and have great advantages in fault tolerance and isolation. Thus, the algorithm can be deemed as practical scheme for integrating different kinds of navigation sensors.