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Yao Tang

Researcher at Texas Tech University

Publications -  11
Citations -  295

Yao Tang is an academic researcher from Texas Tech University. The author has contributed to research in topics: Radar engineering details & Continuous-wave radar. The author has an hindex of 7, co-authored 11 publications receiving 216 citations.

Papers
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Journal ArticleDOI

A Portable FMCW Interferometry Radar With Programmable Low-IF Architecture for Localization, ISAR Imaging, and Vital Sign Tracking

TL;DR: In this article, a portable radar system for short-range localization, inverse synthetic aperture radar imaging, and vital sign tracking is presented, which incorporates frequency-modulated continuous-wave (FMCW) and interferometry (Doppler) modes.
Journal ArticleDOI

Short-Range Doppler-Radar Signatures from Industrial Wind Turbines: Theory, Simulations, and Measurements

TL;DR: In this paper, short-range Doppler radar signatures of wind turbines are both mathematically analyzed and practically verified through simulations and experiments and it is demonstrated that the use of high-frequency radar systems is beneficial in terms of improved spectrogram resolution.
Proceedings ArticleDOI

Short-range indoor localization using a hybrid doppler-UWB system

TL;DR: A novel hybrid indoor localization solution that combines a wearable K-band trajectory-tracking Doppler radar with an ultra-wideband (UWB) positioning system that constantly tracking the trajectory by integrating speed into position change is presented.
Proceedings ArticleDOI

An experimental study on the feasibility of fall prevention using a wearable K-band FMCW radar

TL;DR: An experimental study on a novel fall prevention system using wearable FMCW radar is presented in this paper, attached to the front of a subject's shoe to detect any potential obstacle on the walking path.
Proceedings ArticleDOI

A step forward towards radar sensor networks for structural health monitoring of wind turbines

TL;DR: The convenience of employing high-frequency radar systems for the sensor network and situating the radars on the ground is revealed, which may provide useful information to reliably detect possible defects or malfunctioning of wind turbines.