| Autor: |
Budiman P. A. Rohman, Muhammad Andra, Masahiko Nishimoto |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 6572-6584 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2151-1535 |
| DOI: |
10.1109/JSTARS.2021.3087668 |
| Popis: |
The detection of a human being behind obstacles using radar technology has many promising applications, such as postdisaster search and rescue missions. In the case of large observation areas, the use of an unmanned aerial vehicle as the moving platform for radar is an appealing approach. However, this task is challenging because human vital signs provide a relatively weak signal compared with background noise and clutter. The drone's instability also negatively affects the obtained radar signal. Thus, this article presents a new signal processing method to extract and enhance respiration signals from drone-mounted radar. The method works by extracting the analytic signal representation and applying the subspace component segregation. Laboratory experiments in a controlled environment show that the proposed method can suppress a considerable level of vibration generated by unbalanced motor motion and enhance the respiration signal from radar data. A field experimental study using an octocopter in hovering mode confirms the method performs well in real-world conditions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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