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

TL;DR

This paper introduces a variational message passing method for detecting and estimating respiratory motion from UWB radar signals, significantly improving detection accuracy over traditional FFT-based methods.

Contribution

The paper develops a novel VMP-based approach that models multipath components for contact-free vital sign monitoring, enhancing detection performance.

Findings

Detection probability of 0.95 at -20 dB SNR

Significant improvement over FFT-based detector

Better incorporation of multipath components

Abstract

We present a variational message passing (VMP) 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 by 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, since the multipath components (MPCs) are better incorporated into the detection procedure. Specifically, the proposed method has a detection probability of 0.95 at -20 dB signal-to-noise ratio (SNR), while the estimator-correlator and FFT-based detector have 0.32 and 0.05, respectively.