基于一致性策略的传感器网络分布式滤波器

IF 1.2 Q2 MATHEMATICS, APPLIED

Journal of Applied Mathematics Pub Date : 2013-10-26 DOI:10.1155/2013/683249

Xie Li, Huang Caimou, Hu Haoji

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引用次数: 6

摘要

网络动态系统的一致性算法是传感器网络中数据融合的一个重要研究问题。本文研究了基于卡尔曼共识滤波器和信息共识滤波器的分布式传感器网络状态估计算法。首先，对卡尔曼共识滤波器和信息共识滤波器进行了深入的比较分析，结果表明信息共识滤波器的性能优于卡尔曼共识滤波器。其次，提出了一种基于信息共识过滤器的共识权更新优化过程。最后给出了一些数值模拟，实验结果表明，该方法比现有的共识滤波策略取得了更好的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Distributed Filter with Consensus Strategies for Sensor Networks

Consensus algorithm for networked dynamic systems is an important research problem for data fusion in sensor networks. In this paper, the distributed filter with consensus strategies known as Kalman consensus filter and information consensus filter is investigated for state estimation of distributed sensor networks. Firstly, an in-depth comparison analysis between Kalman consensus filter and information consensus filter is given, and the result shows that the information consensus filter performs better than the Kalman consensus filter. Secondly, a novel optimization process to update the consensus weights is proposed based on the information consensus filter. Finally, some numerical simulations are given, and the experiment results show that the proposed method achieves better performance than the existing consensus filter strategies.

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来源期刊

Journal of Applied Mathematics MATHEMATICS, APPLIED-

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

3.2 months

期刊介绍： Journal of Applied Mathematics is a refereed journal devoted to the publication of original research papers and review articles in all areas of applied, computational, and industrial mathematics.