Towards distortion-tolerant radio-interferometric object tracking

Gergely Zachár, Gyula Simon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Recently radio-interferometric object tracking methods were proposed, which apply inexpensive radio transmitter and receiver nodes to generate and measure radio-interferometric signals. The measured phase values can be used to track the position of one or more moving receivers. In these methods the ideal phase values, calculated from the position of the nodes, are heavily used. Unfortunately, multipath effects in indoor environments can significantly distort the ideal phase values, thus the accuracy and robustness of the former radio-interferometric methods is challenged. In this paper a novel position estimation method is proposed, which is less sensitive and thus more robust to distortions of radio-interferometric space. The performance of the proposed algorithm is compared to that of earlier radio-interferometric object tracking methods using simulations and real measurements.

Original languageEnglish
Title of host publicationSENSORNETS 2016 - Proceedings of the 5th International Confererence on Sensor Networks
Number of pages7
ISBN (Electronic)9789897581694
Publication statusPublished - 2016
Event5th International Confererence on Sensor Networks, SENSORNETS 2016 - Rome, Italy
Duration: Feb 19 2016Feb 21 2016


Other5th International Confererence on Sensor Networks, SENSORNETS 2016


  • Fault tolerance
  • Localization
  • Phase distortion
  • Radio-interferometry
  • Sensor network
  • Tracking

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Fingerprint Dive into the research topics of 'Towards distortion-tolerant radio-interferometric object tracking'. Together they form a unique fingerprint.

  • Cite this

    Zachár, G., & Simon, G. (2016). Towards distortion-tolerant radio-interferometric object tracking. In SENSORNETS 2016 - Proceedings of the 5th International Confererence on Sensor Networks (pp. 207-213). SciTePress.