Design of blind distributed UFIR filter based on average consensus for WSNs

Miguel Vazquez-Olguin, Y. Shmaliy, O. Ibarra-Manzano
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Abstract

Wireless sensor networks (WSNs) often operate under harsh conditions requiring robustness from the estimator. This paper develops a distributed unbiased finite impulse response (UFIR) filter based on average consensus as a more robust alternative to the Kalman filter (KF). Unlike the distributed KF, the distributed UFIR filter typically requires only one consensus filter and completely ignores the noise statistics and initial values. As an example, we consider a vehicle travelling along a circular trajectory under unpredictable impacts and errors in the noise statistics. Better performance of the UFIR filter is demonstrated under diverse operation conditions.
基于平均一致性的wsn盲分布UFIR滤波器设计
无线传感器网络(WSNs)经常在恶劣的条件下工作,需要估计器的鲁棒性。本文提出了一种基于平均一致性的分布无偏有限脉冲响应(UFIR)滤波器,作为卡尔曼滤波器(KF)的鲁棒替代品。与分布式KF不同,分布式UFIR滤波器通常只需要一个共识滤波器,并且完全忽略噪声统计和初始值。作为一个例子,我们考虑在不可预测的冲击和噪声统计误差下沿圆形轨道行驶的车辆。在不同的运行条件下,UFIR滤波器的性能得到了较好的验证。
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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