Distributed Spatial Filtering Over Networked Systems
Distributed Spatial Filtering Over Networked Systems
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DOI：
10.1109/lcsys.2020.3004728
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发表时间：
2021-04
影响因子：
3
通讯作者：
Shinsaku Izumi;Ryosuke Katayama;Xin Xin-Xin;T. Yamasaki
中科院分区：
文献类型：
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作者：
Shinsaku Izumi;Ryosuke Katayama;Xin Xin-Xin;T. Yamasaki
这封信涉及网络系统上的分布式空间滤波，即，经由分布式计算将针对节点给出的信号值变换为具有期望的空间频率特性的信号值。现有的滤波算法只能实现低通滤波特性，限制了其应用范围。为了解决这个问题，我们扩展了上述滤波算法使用一个额外的设计参数。然后，我们提出了一个表征的所有可实现的过滤器特性作为实现分布式空间滤波的充分必要条件。结果表明，扩展算法增加了可实现滤波器特性的范围。仿真和真实的传感器网络去噪实验均验证了该方法的有效性。实验结果表明，该方法有效地降低了空间噪声，并取得了比平均一致性算法和平均滤波器更高的性能。
This letter concerns distributed spatial filtering over networked systems, i.e., transforming signal values given for nodes to those with a desired spatial frequency characteristic via a distributed computation. An existing filtering algorithm can achieve only low-pass filter characteristics, which limits its range of applications. To address this limitation, we extend the aforementioned filtering algorithm using an additional design parameter. We then present a characterization of all the realizable filter characteristics as a necessary and sufficient condition for achieving distributed spatial filtering. As a result, it is shown that the extended algorithm increases the range of the realizable filter characteristics. The proposed method is verified not only by simulation but also by denoising experiments for a real sensor network. The results show that the proposed method effectively reduces spatial noise and achieves higher performance than an average consensus algorithm and an average filter.