期刊
IEEE SENSORS JOURNAL
卷 21, 期 22, 页码 25870-25879出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2021.3117707
关键词
Radar; Radar imaging; Radar measurements; Shadow mapping; Data integration; Sensors; Position measurement; Biomedical engineering; data fusion; radar measurement; radar imaging; radar signal processing
资金
- Japan Society for the Promotion of Science (JSPS) KAKENHI [19H02155, 21H03427]
- Japan Science and Technology Agency (JST) Promoting Individual Research to Nurture the Seeds of Future Innovation and Organizing Unique, Innovative Network (PRESTO) [JPMJPR1873]
- JST Center of Innovation (COI) [JPMJCE1307]
- Grants-in-Aid for Scientific Research [21H03427] Funding Source: KAKEN
This study introduces a data fusion method for multiradar systems to measure the respiration of multiple people at arbitrary positions, overcoming shadowing issues. Experimental results demonstrate the method's capability to accurately measure the respiration of all seven participants, showcasing its effectiveness in simultaneous respiratory measurements of multiple individuals.
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 effectiveness of the proposed method, we performed experiments based on two scenarios with different layouts that involved seven participants and two radar systems. Through these experiments, the proposed method was demonstrated to be capable of measuring the respiration of all seven people by overcoming the shadowing issue. In the two scenarios, the average errors of the proposed method in estimating the respiration rates were 0.33 and 1.24 respirations per minute (rpm), respectively, thus demonstrating accurate and simultaneous respiratory measurements of multiple people using the multiradar system.
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