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Predictive Fusion Weighted Method Based on Multisensor Time-Delay Network

机译:基于多传感器时延网络的预测融合加权方法

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Because the existing fusion methods based on network-delay often use the traditional synchronous fusion algorithms directly, it inevitably induces some problems, such as information delay, resource free, and bad real-time performance etc. Aiming at above problems this paper combined the predictive estimate with the technology of sequential weighted fusion at the basis of the existing research. Accordingly, a new multisensor predictive weighted fusion method which could adapt to network-delay was proposed. The new method can not only avoid the disadvantages existing in the current data fusion method founded on network delay but also gain the better real-time predictive function. It presents the process to deduce the sequential predictive weighted method based on network-delay. Moreover, the computer simulation and theoretical analysis are used to show the practicability and advantage of the proposed fusion method.
机译:由于基于网络延迟的现有融合方法通常直接使用传统的同步融合算法,因此它不可避免地诱导一些问题,例如信息延迟,无资源,以及不良的实时性能等。旨在上述问题本文将预测性结合起来以现有研究的基础估计顺序加权融合技术。因此,提出了一种可以适应网络延迟的新多传感器预测加权融合方法。新方法不仅可以避免在网络延迟上创立的当前数据融合方法中存在的缺点,还可以获得更好的实时预测功能。它呈现了推导率基于网络延迟的顺序预测加权方法的过程。此外,使用计算机仿真和理论分析来展示所提出的融合方法的可行性和优点。

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