Litcius/Paper detail

Fourier Domain Millimeter-Wave Imaging Using Noncooperative 5G Communications Signals

Stavros Vakalis, Serge R. Mghabghab, Jeffrey A. Nanzer

2022IEEE Transactions on Antennas and Propagation22 citationsDOI

Abstract

The spectrum of millimeter-wave frequencies is becoming increasingly crowded due to the advances in fifth-generation (5G) communications and automotive radar, leading to greater interest in spectrum coexistence for functions like sensing and communications. While most research has focused on minimizing interference between sensing and communications, we take a different approach that leverages dense communications signal environments for passive sensing applications. We present a millimeter-wave imaging system that captures information in the spatial frequency (Fourier) domain, similar to concepts used in radio astronomy. In contrast to traditional millimeter-wave sensing and imaging approaches, Fourier-domain image formation is improved as more incoherent signals are included in the environment. In particular, multiple millimeter-wave communications signals generate spatiotemporal incoherence, which enables Fourier-domain sampling and image formation. We present a method for characterizing the imaging efficacy of communications signals in an environment based on new spatiotemporal coherence metrics. We discuss simple solutions to problems of increasing spatial coherence in cases where transmit resources are limited. Finally, we demonstrate a 38 GHz millimeter-wave imaging system capturing 5G communications signals from a set of independent transmitters, demonstrating the ability to image multiple objects in a scene.

Topics & Concepts

Extremely high frequencyComputer scienceFrequency domainCoherence (philosophical gambling strategy)Fourier transformInterference (communication)Communications systemMillimeterTelecommunicationsRemote sensingOpticsComputer visionPhysicsGeographyQuantum mechanicsChannel (broadcasting)Microwave Imaging and Scattering AnalysisTerahertz technology and applicationsSoil Moisture and Remote Sensing