• Login
    View Item 
    •   Home
    • Research
    • Articles
    • View Item
    •   Home
    • Research
    • Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    Accurate 3D Localization Method for Public Safety Applications in Vehicular Ad-hoc Networks

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    08334533.pdf
    Size:
    475.8Kb
    Format:
    PDF
    Description:
    Accepted Manuscript
    Download
    Type
    Article
    Authors
    Ansari, Abdul Rahim
    Saeed, Nasir cc
    Haq, Mian Imtiaz Ul
    Cho, Sunghyun
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2018-04-10
    Online Publication Date
    2018-04-10
    Print Publication Date
    2018
    Permanent link to this record
    http://hdl.handle.net/10754/627599
    
    Metadata
    Show full item record
    Abstract
    Vehicular ad hoc networks (VANETs) represent a very promising research area because of their ever increasing demand, especially for public safety applications. In VANETs vehicles communicate with each other to exchange road maps and traffic information. In many applications, location-based services are the main service, and localization accuracy is the main problem. VANETs also require accurate vehicle location information in real time. To fulfill this requirement, a number of algorithms have been proposed; however, the location accuracy required for public safety applications in VANETs has not been achieved. In this paper, an improved subspace algorithm is proposed for time of arrival (TOA) measurements in VANETs localization. The proposed method gives a closed-form solution and it is robust for large measurement noise, as it is based on the eigen form of a scalar product and dimensionality. Furthermore, we developed the Cramer-Rao Lower Bound (CRLB) to evaluate the performance of the proposed 3D VANETs localization method. The performance of the proposed method was evaluated by comparison with the CRLB and other localization algorithms available in the literature through numerous simulations. Simulation results show that the proposed 3D VANETs localization method is better than the literature methods especially for fewer anchors at road side units and large noise variance.
    Citation
    Ansari AR, Saeed N, Haq MIU, Cho S (2018) Accurate 3D Localization Method for Public Safety Applications in Vehicular Ad-hoc Networks. IEEE Access: 1–1. Available: http://dx.doi.org/10.1109/ACCESS.2018.2825371.
    Sponsors
    This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2015R1D1A1A01059473).
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Access
    DOI
    10.1109/ACCESS.2018.2825371
    Additional Links
    https://ieeexplore.ieee.org/document/8334533/
    ae974a485f413a2113503eed53cd6c53
    10.1109/ACCESS.2018.2825371
    Scopus Count
    Collections
    Articles; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

    entitlement

     
    DSpace software copyright © 2002-2023  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.