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Asynchronous multi-sensor hierarchical adaptive data fusion algorithm

机译:异步多传感器分层自适应数据融合算法

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This paper presents an adaptive hierarchical data fusion algorithm for asynchronous multi-rate sensor. The proposed algorithm is different from general hierarchical fusion methods. Not only current values and previous values of local estimates but also the previous outputs of the global fusion are used for the global estimate. The global fusion adaptively selects local estimates for the center estimate by the introduction of mapping matrices. The innovation of the global fusion is adaptively adjusted with information-sharing coefficients. When failed to the local estimate, the predictive value of the local estimate will displace the estimate, and it is used for the global fusion. The global fusion algorithm is achieved. Simulation results demonstrated the effectiveness of the algorithm.
机译:本文提出了一种用于异步多速率传感器的自适应分层数据融合算法。该算法不同于一般的分层融合方法。不仅本地估计的当前值和先前值,而且全局融合的先前输出也用于全局估计。全局融合通过引入映射矩阵来自适应地为中心估计选择局部估计。全球融合的创新通过信息共享系数进行自适应调整。当局部估计失败时,局部估计的预测值将替换该估计,并将其用于全局融合。实现了全局融合算法。仿真结果证明了该算法的有效性。

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