Accurate Measurement of Human Vital Signs With Linear FMCW Radars Under Proximity Stationary Clutters

Area of Science:

• Radar Signal Processing
• Biomedical Engineering
• Electromagnetics

Background:

• Vital sign detection using radar is challenged by stationary clutter.
• Existing methods for LFMCW radar struggle with proximity interference.

Purpose of the Study:

• To develop a novel technique for synthesizing slow-time I/Q signals from single-channel LFMCW radar.
• To adapt existing clutter removal techniques for LFMCW vital sign detection.

Main Methods:

• Synthesizing slow-time I/Q signals equivalent to quadrature CW radar.
• Translating stationary clutter to DC offsets in synthesized signals.
• Applying circle-fitting based DC offsets calibration (DCcal) and modified differentiate and cross-multiply (MDACM) algorithms.

Main Results:

• Proximity stationary clutters are effectively translated to DC offsets.
• DCcal technique successfully eliminates clutter impact in LFMCW radar.
• MDACM algorithm resolves phase ambiguity issues.
• Millimeter-wave radar experiments demonstrate micrometer-level accuracy for vital signs and mechanical vibration extraction.

Conclusions:

• The proposed technique enables accurate vital sign detection with LFMCW radar even in cluttered environments.
• The method provides a robust solution for overcoming stationary clutter limitations.
• This advancement has significant implications for non-contact health monitoring.