Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals

Jakob Möderl*, Erik Leitinger, Franz Pernkopf, Klaus Witrisal

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

We present a variational message passing (VMP)-based approach to detect the presence of a person based on their respiratory chest motion using multistatic ultra-wideband (UWB) radar. In the process, the respiratory motion is estimated for contact-free vital sign monitoring. The received signal is modeled as a backscatter channel and the respiratory motion and propagation channels are estimated using VMP. We use the evidence lower bound (ELBO) to approximate the model evidence for the detection. Numerical analyses and measurements demonstrate that the proposed method leads to a significant improvement in the detection performance compared to a fast Fourier transform (FFT)-based detector or an estimator-correlator in low-signal-to-noise ratio (SNR) conditions, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at −20dB SNR, while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively.
Originalspracheenglisch
TitelICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
Seitenumfang5
ISBN (elektronisch)9781728163277
DOIs
PublikationsstatusVeröffentlicht - 7 Juni 2023
Veranstaltung48th IEEE International Conference on Acoustics, Speech, and Signal Processing: ICASSP 2023 - Rhodos, Griechenland
Dauer: 4 Juni 20239 Juni 2023

Publikationsreihe

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Band2023-June
ISSN (Print)1520-6149

Konferenz

Konferenz48th IEEE International Conference on Acoustics, Speech, and Signal Processing
KurztitelICASSP 2023
Land/GebietGriechenland
OrtRhodos
Zeitraum4/06/239/06/23

ASJC Scopus subject areas

  • Software
  • Signalverarbeitung
  • Elektrotechnik und Elektronik

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