Time-of-Arrival Estimation for Positioning in Bandwidth-Limited Dense Multipath Channels

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For time-of-flight-based wireless positioning systems operating in (dense) multipath propagation channels, the accuracy is severely influenced by the signal bandwidth, because the dense multipath component (DMC) interferes with the desired, information-bearing line-of-sight (LoS) signal. Several such systems make use of bandwidth-limited frequency resources, e.g. the industrial, scientific and medical (ISM) bands, therefore the achievable position estimation accuracy is limited. In this paper, we propose a model-based delay-estimation method which takes into account a parametric model of the DMC and thus exploits the signal energy carried in the DMC. The resulting algorithm exhibits an enhanced delay estimation accuracy and remarkable robustness in non-LoS situations. The algorithm is benchmarked against a maximum likelihood (ML) estimator not incorporating a model for the DMC and against the estimated Cramér-Rao lower bound (CRLB) in presence of DMC. Results show a significant performance gain for scenarios where the conventional ML estimator performs poorly. An evaluation of measurement data validates the simulation, showing a root-mean-square error (RMSE) of 33.4 cm compared to 1.89 m for the conventional ML estimator, at a signal bandwidth of 80 MHz.
Original languageEnglish
Title of host publication2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication, SPAWC 2022
PublisherIEEE Xplore
Number of pages5
ISBN (Electronic)9781665494557
ISBN (Print)978-1-6654-9456-4
Publication statusPublished - 6 Jul 2022
Event23rd IEEE International Workshop on Signal Processing Advances in Wireless Communication: SPAWC 2022 - Oulu, Finland
Duration: 4 Jul 20226 Jul 2022


Conference23rd IEEE International Workshop on Signal Processing Advances in Wireless Communication


  • Cramér-Rao lower bound
  • delay estimation
  • Indoor localization
  • ranging
  • time of flight

ASJC Scopus subject areas

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

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