STATE ESTIMATION FOR TWO-LEVEL HYBRID MULTISENSOR DATA FUSION SYSTEMS
两级混合多传感器信息融合中的状态估计

In hybrid multisensor systems where a part of sensors processes their data locally to produce local tracks, another part of sensors only provides detection reports, the tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. This paper presents a globally optimal composite filtering solution for a two-level hybrid multisensor system. It is shown that the fusion center first needs to fuse the local estimates from the L sensors, and then to update recursively the fused track by using a Kalman filter based on the observations of the other N-L sensors. This paper also considers the estimation problems based on the different Cartesian coordinates.