Multiradar Data Fusion for Respiratory Measurement of Multiple People
Shunsuke Iwata, Takato Koda, and Takuya Sakamoto

TL;DR
This paper introduces a multiradar data fusion technique that accurately measures the respiration rates of multiple people at arbitrary positions, overcoming shadowing issues without prior knowledge of radar layouts.
Contribution
The study presents a novel method for multiradar data fusion that estimates radar layouts and measures multiple respiratory signals simultaneously without prior positional information.
Findings
Successfully measured respiration of 7 people in experiments.
Achieved average respiration rate errors of 0.33 and 1.24 rpm.
Demonstrated robustness against shadowing effects.
Abstract
This study proposes a data fusion method for multiradar systems to enable measurement of the respiration of multiple people located at arbitrary positions. Using the proposed method, the individual respiration rates of multiple people can be measured, even when echoes from some of these people cannot be received by one of the radar systems because of shadowing. In addition, the proposed method does not require information about the positions and orientations of the radar systems used because the method can estimate the layout of these radar systems by identifying multiple human targets that can be measured from different angles using multiple radar systems. When a single target person can be measured using multiple radar systems simultaneously, the proposed method selects an accurate signal from among the multiple signals based on the spectral characteristics. To verify the…
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Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · Indoor and Outdoor Localization Technologies · Hemodynamic Monitoring and Therapy
