Federated Kalman consensus filter in distributed track fusion

Multi-sensor tracking fusion plays a fundamental role in networked information system, especially in the field of fire control systems. According to the diversity, networked and flexible recombined characteristics of the modern information system, a bottom-up architecture of networked information system and the method of track fusion are investigated. Distributed track fusion problem under limited communication is discussed, and federated Kalman consensus filtering(FKCF) algorithm is proposed. Compared to conventional federated filter, FKCF algorithm considers the mobile sensor model, applies Kalman consensus filter to design the sub-filter and designs information-driven method to improve information allocation. The algorithm not only achieves auto recombination and improves survivability, but increases fused tracking accuracy of mobile sensor network with limited communication capability. The experimental results show that FKCF algorithm is better than conventional federated filtering algorithm in track fusion with limited communication.