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Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks
This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168470/ https://www.ncbi.nlm.nih.gov/pubmed/24977387 http://dx.doi.org/10.3390/s140711444 |
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author | Cao, Meng-Li Meng, Qing-Hao Zeng, Ming Sun, Biao Li, Wei Ding, Cheng-Jun |
author_facet | Cao, Meng-Li Meng, Qing-Hao Zeng, Ming Sun, Biao Li, Wei Ding, Cheng-Jun |
author_sort | Cao, Meng-Li |
collection | PubMed |
description | This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source. |
format | Online Article Text |
id | pubmed-4168470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41684702014-09-19 Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks Cao, Meng-Li Meng, Qing-Hao Zeng, Ming Sun, Biao Li, Wei Ding, Cheng-Jun Sensors (Basel) Article This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source. MDPI 2014-06-27 /pmc/articles/PMC4168470/ /pubmed/24977387 http://dx.doi.org/10.3390/s140711444 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Cao, Meng-Li Meng, Qing-Hao Zeng, Ming Sun, Biao Li, Wei Ding, Cheng-Jun Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title | Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title_full | Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title_fullStr | Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title_full_unstemmed | Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title_short | Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks |
title_sort | distributed least-squares estimation of a remote chemical source via convex combination in wireless sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168470/ https://www.ncbi.nlm.nih.gov/pubmed/24977387 http://dx.doi.org/10.3390/s140711444 |
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