Millimeter-Wave Multi-Radar Tracking System Enabled by a Modified GRIN Luneburg Lens for Real-Time Healthcare Monitoring
Mohammad Omid Bagheri, Justin Chow, Josh Visser, Veronica Leong, George Shaker
TL;DR
The paper tackles the challenge of real-time, non-contact healthcare monitoring with wide angular coverage by introducing a Multi-Radar Modified GRIN Luneburg Lens (MMLL). It combines five 58–63 GHz FMCW radar modules arranged around a rod-based, anisotropic GRIN lens to produce multiple fixed high-gain beams without steering, synchronized by a Python-based framework. The design achieves approximately 12 dB realized gain per path and 140° coverage, validated by full-wave simulations and a 10 cm prototype, with fall detection demonstrated in a real environment. The system integrates a back-end fusion engine and a real-time GUI for seamless multi-zone tracking and alerts, offering a compact, low-cost, scalable platform for ambient healthcare and smart environments.
Abstract
Multi-beam radar sensing systems are emerging as powerful tools for non-contact motion tracking and vital-sign monitoring in healthcare environments. This paper presents the design and experimental validation of a synchronized millimeter-wave multi-radar tracking system enhanced by a modified spherical gradient-index (GRIN) Luneburg lens. Five commercial FMCW radar modules operating in the 58--63 GHz band are arranged in a semi-circular configuration around the lens, whose tailored refractive-index profile accommodates bistatic radar modules with co-located transmit (TX) and receive (RX) antennas. The resulting architecture generates multiple fixed high-gain beams with improved angular resolution and minimal mutual interference. Each radar operates independently but is temporally synchronized through a centralized Python-based acquisition framework to enable parallel data collection and low-latency motion tracking. A 10-cm-diameter 3D-printed prototype demonstrates a measured gain enhancement of approximately 12 dB for each module, corresponding to a substantial improvement in detection range. Full-wave simulations and measurements confirm effective non-contact, privacy-preserving short-range human-motion detection across five 28-degree sectors, providing 140-degree total angular coverage. Fall-detection experiments further validate reliable wide-angle performance and continuous spatial tracking. The proposed system offers a compact, low-cost, and scalable platform for millimeter-wave sensing in ambient healthcare and smart-environment applications.
