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Optimal state estimation for a class of asynchronous multirate multisensor dynamic systems

机译:一类异步多速率多传感器动态系统的最优状态估计

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To fuse information observed by asynchronous multirate sensors, a hybrid data fusion framework is presented. By use of the presented framework, information from different sensors may be fused effectively. To generate the optimal state estimate, the method is implemented by prediction and two times update in sequence. The information observed by the sensor with the highest sampling rate in the finest scale is used to update the state prediction, and the re-innovation is taken by use of the sensors with lower sampling rates at coarser scales. The process is carried out successively, and the fused state estimate at the finest scale is generated. The effectiveness of the algorithm is illustrated through theoretical proof and simulation results.
机译:为了融合异步多速率传感器观察到的信息,提出了一种混合数据融合框架。通过使用提出的框架,可以有效地融合来自不同传感器的信息。为了生成最佳状态估计,该方法通过预测来实现,并按顺序两次更新。传感器以最佳比例在最高采样率下观察到的信息用于更新状态预测,而在较低尺度下以较低采样率的传感器进行重新创新。依次执行该过程,并生成最细规模的融合状态估计。通过理论证明和仿真结果说明了该算法的有效性。

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