IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v15y2019i7p1550147719858591.html
   My bibliography  Save this article

Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position errors

Author

Listed:
  • Ruirui Liu
  • Ding Wang
  • Jiexin Yin
  • Ying Wu

Abstract

Based on measurements of angle of arrival and time difference of arrival, a method is proposed to improve the accuracy of localization with imperfect sensors. A derivation of the Cramér–Rao lower bound and the root mean square error is presented aimed at demonstrating the significance of taking synchronization errors into consideration. Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. The theoretical performance of the constrained total least squares localization algorithm subject to sensor position errors and synchronization clock bias is derived, and a framework for the performance analysis is developed. In addition, the first-order error analysis illustrates that the proposed method can achieve the Cramér–Rao lower bound under moderate Gaussian noises by a mathematic derivation. Finally, simulation results are presented that verify the validity of the theoretical derivation and superiority of the new algorithm.

Suggested Citation

  • Ruirui Liu & Ding Wang & Jiexin Yin & Ying Wu, 2019. "Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position errors," International Journal of Distributed Sensor Networks, , vol. 15(7), pages 15501477198, July.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:7:p:1550147719858591
    DOI: 10.1177/1550147719858591
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147719858591
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147719858591?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:15:y:2019:i:7:p:1550147719858591. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.