Radar-Based Identification of Individuals Using Heartbeat Features Extracted from Signal Amplitude and Phase

TL;DR

This paper introduces a non-contact radar-based method for individual identification using heartbeat features extracted from amplitude, phase, and complex signals, achieving high accuracy through feature fusion.

Contribution

It evaluates the contribution of amplitude, phase, and complex signals in heartbeat-based identification and proposes a fusion method to improve accuracy.

Findings

Achieved 97.67% identification accuracy with radar signals.

Demonstrated the effectiveness of component-wise analysis and fusion.

Provided insights into the roles of amplitude and phase in identification.

Abstract

This study proposes a non-contact method for identifying individuals through the use of heartbeat features measured with millimeter-wave radar. Although complex-valued radar signal spectrograms are commonly used for this task, little attention has been paid to the choice of signal components, namely, whether to use amplitude, phase, or the complex signal itself. Although spectrograms can be constructed independently from amplitude or phase information, their respective contributions to identification accuracy remain unclear. To address this issue, we first evaluate identification performance using spectrograms derived separately from amplitude, phase, and complex signals. We then propose a feature fusion method that integrates these three representations to enhance identification accuracy. Experiments conducted with a 79-GHz radar system and involving six participants achieved an identification accuracy of 97.67%, demonstrating the effectiveness of the proposed component-wise analysis and integration approach.