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  • 标题:Development of a Robust UFIR Filter with Consensus on Estimates for Missing Data and unknown noise statistics over WSNs
  • 本地全文:下载
  • 作者:Miguel Vazquez-Olguin ; Yuriy S. Shmaiy ; Oscar Ibarra-Manzano
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2019
  • 卷号:292
  • 页码:1-6
  • DOI:10.1051/matecconf/201929204003
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Wireless sensor networks (WSN) are often deployed in harsh environments, where electromagnetic interference, damaged sensors, or the landscape itself cause the network to suffer from faulty links and missing data. In this paper, we develop an unbiased finite impulse response (UFIR) filtering algorithm for optimal consensus on estimates in distributed WSN. Simulations are provided assuming two possible scenarios with missing data. The results show that the distributed UFIR filter is more robust than the distributed Kalman filter against missing data.
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