Distributed robust RLS estimation algorithm over sensor networks

In the parameter estimation of the sensor network, there may be impact noise or pulse interference in the measurement environment, which leads to the outliers that greatly deviate from the actual range, so that the effective parameter estimation problem can't be obtained. A distributed RLS esti...

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Main Authors: Kaikai KANG, Zhaoting LIU, Yingbiao YAO
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2019-01-01
Series:Dianxin kexue
Subjects:
Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019002/
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author Kaikai KANG
Zhaoting LIU
Yingbiao YAO
author_facet Kaikai KANG
Zhaoting LIU
Yingbiao YAO
author_sort Kaikai KANG
collection DOAJ
description In the parameter estimation of the sensor network, there may be impact noise or pulse interference in the measurement environment, which leads to the outliers that greatly deviate from the actual range, so that the effective parameter estimation problem can't be obtained. A distributed RLS estimation algorithm based on node cooperation and robustness was proposed. The characteristic of interference or attack on a node is usually sporadic (ie, sparse) for a period of time was utilized, ℓ<sub>1</sub>norm was introduced to cost function. The outliers which may exist in the measurement data were identified and eliminated, and the interaction between the nodes of the network was utilized to further improve the performance of the parameter estimation. The computer simulation experiments show that the algorithm has good estimation performance.
format Article
id doaj-art-9c98e0197e474120a660f34f4888fde8
institution Kabale University
issn 1000-0801
language zho
publishDate 2019-01-01
publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-9c98e0197e474120a660f34f4888fde82025-01-15T03:03:26ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012019-01-0135374359591399Distributed robust RLS estimation algorithm over sensor networksKaikai KANGZhaoting LIUYingbiao YAOIn the parameter estimation of the sensor network, there may be impact noise or pulse interference in the measurement environment, which leads to the outliers that greatly deviate from the actual range, so that the effective parameter estimation problem can't be obtained. A distributed RLS estimation algorithm based on node cooperation and robustness was proposed. The characteristic of interference or attack on a node is usually sporadic (ie, sparse) for a period of time was utilized, ℓ<sub>1</sub>norm was introduced to cost function. The outliers which may exist in the measurement data were identified and eliminated, and the interaction between the nodes of the network was utilized to further improve the performance of the parameter estimation. The computer simulation experiments show that the algorithm has good estimation performance.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019002/sensor networkrobustnessdistributed processingadaptive estimation
spellingShingle Kaikai KANG
Zhaoting LIU
Yingbiao YAO
Distributed robust RLS estimation algorithm over sensor networks
Dianxin kexue
sensor network
robustness
distributed processing
adaptive estimation
title Distributed robust RLS estimation algorithm over sensor networks
title_full Distributed robust RLS estimation algorithm over sensor networks
title_fullStr Distributed robust RLS estimation algorithm over sensor networks
title_full_unstemmed Distributed robust RLS estimation algorithm over sensor networks
title_short Distributed robust RLS estimation algorithm over sensor networks
title_sort distributed robust rls estimation algorithm over sensor networks
topic sensor network
robustness
distributed processing
adaptive estimation
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000−0801.2019002/
work_keys_str_mv AT kaikaikang distributedrobustrlsestimationalgorithmoversensornetworks
AT zhaotingliu distributedrobustrlsestimationalgorithmoversensornetworks
AT yingbiaoyao distributedrobustrlsestimationalgorithmoversensornetworks