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  <doc>
    <id>1514</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>61</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>bachelorthesis</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2022-06-02</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>2022-04-08</thesisDateAccepted>
    <title language="eng">Self-Calibration of lateration-based localization systems</title>
    <abstract language="eng">Localization systems play an essential role in many applications nowadays; they are implemented in industrial, commercial, and even personal applications; it is always essential for some applications to pinpoint the location of a person or an object in space. In this thesis, I focus on lateration-based localization systems consisting of several stationary nodes or stations and several mobile stations or devices. Lateration techniques are used to find the relative distances between the static nodes and the mobile devices, such as time of arrival (TOA), time difference of arrival (TDoA), and round-trip time (RTT).&#13;
The location of the static nodes needs to be known to find the mobile device's location; thus, the system needs to be calibrated by entering the exact location of the static component to find the location of the mobile devices.&#13;
In this thesis, I discuss the possibility of self-calibrating a lateration-based localization system by taking the relative measurements of a mobile device to the static nodes at random times without initially knowing either the mobile device's location or the locations of the static nodes.&#13;
After modeling the system mathematically, I show that it is possible to detect the positions of the static nodes by deriving a nonlinear model of the geometric configuration that can be solved after making several assumptions by using numerical and optimization approaches, such as the trial-and-error or the Levenberg-Marquardt algorithm, it is possible to detect the positions of the static nodes; however, there are some limitations to this method as it requires a certain number of static nodes and a minimum number of recorded measurements to be able to find a unique solution to the system; these constraints differ depending on the nature of the system and the lateration technique used to record the measurements.</abstract>
    <identifier type="urn">urn:nbn:de:hbz:1383-opus4-15148</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>CC BY-NC-SA 4.0 International - Namensnennung-Nicht kommerziell-Weitergabe unter gleichen Bedingungen</licence>
    <author>Ahmed Ashour</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Self-Calibration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Localization systems</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Lateration techniques</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <thesisGrantor>Hochschule Rhein-Waal</thesisGrantor>
    <file>https://opus4.kobv.de/opus4-rhein-waal/files/1514/Ashour_Bachelor_Thesis_25904.pdf</file>
  </doc>
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