Dynamic Estimation of Vital Signs with mm-wave FMCW Radar

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In this paper, we propose a method for continuous monitoring of vital signs-in particular, respiration frequency-with a commercial mm-wave radar. The nearly constant frequency (NCF) model is adopted to represent chest displacement due to respiration and simulate radar response. Based on this model, an extended Kalman filter (EKF) based estimator is developed to track the breathing frequency of a person. The impact of dynamic model parameters is investigated in numerical simulation. The possibility to track breathing frequency with the proposed method is demonstrated by experimental data processing.

Original languageEnglish
Title of host publicationEuRAD 2020 - 2020 17th European Radar Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9782874870613
Publication statusPublished - 2021
Event17th European Radar Conference, EuRAD 2020 - Utrecht, Netherlands
Duration: 13 Jan 202115 Jan 2021

Publication series

NameEuRAD 2020 - 2020 17th European Radar Conference


Conference17th European Radar Conference, EuRAD 2020

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • extended Kalman filter (EKF)
  • sequential estimation
  • Vital signs


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