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The fusion methods of multi-sensor system based on pseudo-measurement model library

机译:基于伪测量模型库的多传感器系统融合方法

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摘要

For single sensor system, information transmitted in wireless networks will appear the phenomenon of delay, out-of-sequence even dropout, so that the process center cannot receive and handle with the information promptly and effectively. Similarly, this situation also exists in the multi-sensor system where the information needs to be transported by wireless networks, even more severe. As a result, the complexity of the information processing methods for multi-sensor systems is more severe. The core difficulty of these methods is how to deal with the information with the phenomena mentioned above, that not only need to consider the coupling of the sensor itself, but also need to consider the underlying coupling between different sensors. In order to deal with the delay measurements in multisensor systems, this paper builds a novel pseudo-measurement model library which is corresponding to multi-sensor system, then proposes two fusion filtering algorithms to deal with the networked measurements accurately in real time: matrix fusion filter algorithm, centralized filter algorithm. Meanwhile, the final simulation examples demonstrate the effectiveness of the two proposed methods.
机译:对于单传感器系统,在无线网络中传输的信息将出现延迟,失序甚至丢失的现象,从而使处理中心无法及时有效地接收和处理信息。类似地,这种情况在多传感器系统中也存在,在该系统中,信息需要通过无线网络传输,甚至更为严重。结果,用于多传感器系统的信息处理方法的复杂性更加严重。这些方法的核心困难是如何处理具有上述现象的信息,这不仅需要考虑传感器本身的耦合,而且还需要考虑不同传感器之间的潜在耦合。为了处理多传感器系统中的延迟测量,本文建立了一个与多传感器系统相对应的伪测量模型库,然后提出了两种融合滤波算法来实时准确地处理网络测量:矩阵融合过滤算法,集中式过滤算法。同时,最后的仿真实例证明了两种方法的有效性。

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