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dc.contributor.authorMei, Xiaojun
dc.contributor.authorWu, Huafeng
dc.contributor.authorSaeed, Nasir
dc.contributor.authorMa, Teng
dc.contributor.authorXian, Jiangfeng
dc.contributor.authorChen, Yanzhen
dc.date.accessioned2020-08-24T08:20:53Z
dc.date.available2020-08-24T08:20:53Z
dc.date.issued2020-08-20
dc.date.submitted2020-07-17
dc.identifier.citationMei, X., Wu, H., Saeed, N., Ma, T., Xian, J., & Chen, Y. (2020). An Absorption Mitigation Technique for Received Signal Strength-Based Target Localization in Underwater Wireless Sensor Networks. Sensors, 20(17), 4698. doi:10.3390/s20174698
dc.identifier.issn1424-8220
dc.identifier.pmid32825318
dc.identifier.doi10.3390/s20174698
dc.identifier.urihttp://hdl.handle.net/10754/664783
dc.description.abstractLocalization is an indispensable technology for underwater wireless sensor networks (UWSNs). In what concerns UWSNs, the accurate location information is not only the requirement of the marine field applications but also the basis of the other corresponding research, for instance, network routing and topology control. Recently, an astonishing surge of interest has been drawn in the received signal strength (RSS)-based scheme due to cost-effectiveness and synchronization-free compared with others. However, unlike the terrestrial wireless sensor networks (WSNs), the acoustic signal may suffer the absorption loss in the underwater environment besides the path loss, which degrades the localization accuracy and limits the capability of the RSS-based technology in UWSNs. In this context, a robust localization method with an absorption mitigation technique (AMT) is developed. First, an RSS-based analytically tractable measurement model is conducted, where the maximum likelihood estimator (MLE) is derived. Nevertheless, it is quite challenging to solve the problem using MLE under a non-convex expression. Therefore, by exploiting certain approximations, the considered localization problem is converted into an optimization expression with a maximum absorption loss involved. A min-max strategy is then presented, with which the problem is turned to minimize the worst situation of the absorption loss. After a simple manipulation, the problem is further investigated as a generalized trust region sub-problem (GTRS) framework. Although the GTRS is a non-convex scheme, the solution can be obtained through an iteration method by introducing a multiplier. In addition, the closed-form expression of the Cramer-Rao lower bound (CRLB) of the analytically tractable measurement model is derived. Numerical simulations demonstrate the effectiveness of the proposed method compared with the state-of-the-art approaches in different scenarios.
dc.description.sponsorshipThis work was supported by the National Natural Science Foundation of China (Grant No.51579143, 61673117), the Shanghai Committee of Science and Technology, China (Grant No. 18040501700), Postdoctoral Science Foundation of China (Grant No. 2020M670887), the top-notch innovative program for postgraduates of Shanghai Maritime University (Grant No.2019YBR002, 2019YBR006), the postgraduate innovation foundation of Shanghai Maritime University (Grant No.2017ycx030, 2016ycx042), and the China Scholarship Council (CSC).
dc.publisherMDPI AG
dc.relation.urlhttps://www.mdpi.com/1424-8220/20/17/4698
dc.rightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleAn Absorption Mitigation Technique for Received Signal Strength-Based Target Localization in Underwater Wireless Sensor Networks.
dc.typeArticle
dc.contributor.departmentComputer, Electrical, Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia.
dc.identifier.journalSensors (Basel, Switzerland)
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionMerchant Marine College, Shanghai Maritime University, Shanghai 201306, China.
dc.contributor.institutionInstitute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, Portugal.
dc.contributor.institutionScience and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China.
dc.contributor.institutionDepartment of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy.
dc.identifier.volume20
dc.identifier.issue17
dc.identifier.pages4698
kaust.personSaeed, Nasir
dc.date.accepted2020-08-18
refterms.dateFOA2020-08-24T08:22:00Z


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