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摘要: 提出了一种基于一致性的分布式滤波算法, 针对实际应用中存在的网络丢包问题, 重点研究了有丢包时的分布式滤波算法, 通过理论分析给出了估计误差系统收敛的充分条件. 应用数值仿真将本 文提出的算法与已有的经典滤波算法分别在理想状况与有丢包状况时进行比较, 研究表明本算法在丢包时具有较优的滤波效果. 并进一步研究了一致性步长对估计误差协方差的影响, 发现存在估计误差达到最小值的最优步长. 最后, 研究了丢包率对算法的影响, 发现起``领导''作用的传感器在滤波时发挥重要作用, 可通过控制这些传感器的丢包率来减小丢包对整个网络系统的影响.Abstract: This paper introduces a consensus-based distributed filtering algorithm. Aiming at the problem of network packet-dropping in practical applications, we focus on the distributed filtering algorithm with packet-dropping. By theoretical analysis, we give a sufficient condition for the convergence of the estimation error system. We compare our algorithm with a classical filtering one by some simulations in ideal and packet-dropping cases, respectively. The results show that our algorithm does better filtering in the packet-dropping case. Furthermore, we study the influence of the consensus step-size on the estimation error covariance, and find out that an optimal step-size may lead to the minimum of estimation error covariance. Finally, we study the influence of the packet-dropping rate on our algorithm, and find that the leaders of the sensors play an important role in the filtering. We can decrease the influence of the packet-dropping on the whole network system by controlling the packet-dropping rate of the leaders.
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Key words:
- Distributed filtering /
- consensus algorithm /
- Kalman filtering /
- sensor network /
- multi-agent system
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