分布式联邦滤波器在多传感器信息融合领域得到广泛的重视，联邦滤波中的信息分配原则直接影响滤波器的精度和容错性，而常规的标量形式联邦滤波信息分配方法无法满足高动态环境下状态的动态变化特性。信息分配是设计和实现联邦滤波器的关键环节，基于系统误差协方差阵和可观测阵。文中考虑系统状态估计精度和系统的可观测性，提出了一种新的联邦滤波信息分配方案和算法。新的联邦滤波算法允许每一个系统状态变量具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。仿真结果表明，与传统联邦滤波算法比较，改进的信息融合算法精度能提高30％以上。% Decentralized federated filter has significant application in the field of multi-sensor information fusion, and information distribution rule can directly affect the precision and fault tolerance. However, the conventional scalar form of information distribution scheme for federated filter can not satisfy the dynamic state changes under high-dynamic environment. In this paper, a new information distribution scheme is proposed based on the error covariance matrix and the observability matrix, which takes into account the estimation accuracy of system state and the observability of the system. This new algorithm allows each system state variables to have different real-time information distribution factors, and hence improves the estimation accuracy of the Federated Filter. The simulation show that the information sharing algorithm can improved filter precision above 30%.
展开▼
