Sequential Estimator for Breathing and Heart Beat Frequencies Using Radar

Master Thesis (2019)
Author(s)

Guigeng Su (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Alexander Yarovoy – Mentor (Microwave Sensing, Signals & Systems)

Nikita Petrov – Graduation committee member (Microwave Sensing, Signals & Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2019
Language
English
Graduation Date
28-08-2019
Awarding Institution
Delft University of Technology
Programme
Electrical Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
Page Views
400
Collections
thesis
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Abstract

With an LFMCW automotive radar operating at its center frequency of 77GHz, the sequential estimation of frequency and amplitude for vital signs, namely, respiration and heartbeat, are considered. The radar response of vital signs is described and analyzed. With extraction of the phase history, extended Kalman filter and particle filter are simulated. Extended Kalman filter with a certain number of samples per iteration performs well for sequential estimating the respiratory frequency and amplitude in different scenarios. This sequential estimator is then verified by experimental data.

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