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在混合式多传感器信息融合系统中,一部分传感器通过处理它们的数据产生局部航迹,另一部分传感器则只提供检测报告,这些航迹和检测报告被传送到融合中心完成航迹融合和组合滤波。本文提出适合于两级混合式多传感器系统的全局最优状态估计解。在这种结构中,融合中心首先需要融合来自L个传感器的局部估计,然后基于其它N-L个传感器的观测,利用Kalman滤波技术依次更新已融合的航迹。本文还考虑了各传感器分布在不同地理位置时的状态估计问题。
In the hybrid multi-sensor information fusion system, some sensors generate local tracks by processing their data, while others provide only detection reports. These tracks and inspection reports are sent to the fusion center to complete the track fusion and combined filtering. In this paper, we propose a global optimal state estimator suitable for a two-stage hybrid multisensor system. In this architecture, the fusion center first needs to fuse the local estimates from the L sensors and then update the fused tracks sequentially using Kalman filtering techniques based on the observations of the other N-L sensors. In this paper, we also consider the state estimation of each sensor in different geographical locations.