Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model
Unmanned Aerial Vehicle (UAV) robot microwave imaging systems have attracted comprehensive attention. Compared with visible light and infrared imaging systems, microwave imaging is not susceptible to weather. Active microwave imaging systems have been realized in UAV robots. However, the scattering...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/22/8736 |
| _version_ | 1797464011874238464 |
|---|---|
| author | Zhihua Chen Xinya Qiao Pei Wu Tiancai Zhang Tao Hong Linquan Fang |
| author_facet | Zhihua Chen Xinya Qiao Pei Wu Tiancai Zhang Tao Hong Linquan Fang |
| author_sort | Zhihua Chen |
| collection | DOAJ |
| description | Unmanned Aerial Vehicle (UAV) robot microwave imaging systems have attracted comprehensive attention. Compared with visible light and infrared imaging systems, microwave imaging is not susceptible to weather. Active microwave imaging systems have been realized in UAV robots. However, the scattering signals of geographical objects from satellite transmitting systems received by UAV robots to process imaging is studied rarely, which reduces the need of load weight for the UAV robot. In this paper, a multi-path scattering model of vegetation on the earth surface is proposed, and then the microwave imaging algorithm is introduced to reconstruct the images from the UAV robot receiving the scattering data based on the multi-path model. In image processing, it is assumed that the orbit altitude of a transmitter loaded on the satellite remains unchanged, and the receiver loaded UAV robot obtains the reflective information from ground vegetation with different zenith angles. The imaging results show that the angle change has an impact on the imaging resolution. The combination of electromagnetic scattering model and image processing method contributes to understanding the image results and the multi-path scattering mechanisms of vegetation, which provide a reference for the research and development of microwave imaging systems of UAV robot networking using satellite transmitting signals. |
| first_indexed | 2024-03-09T18:00:52Z |
| format | Article |
| id | doaj.art-4a1bf51a45994e3dae2abde37ee72e1c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T18:00:52Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-4a1bf51a45994e3dae2abde37ee72e1c2023-11-24T09:54:58ZengMDPI AGSensors1424-82202022-11-012222873610.3390/s22228736Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering ModelZhihua Chen0Xinya Qiao1Pei Wu2Tiancai Zhang3Tao Hong4Linquan Fang5Southwest Technology and Engineering Research Institute, Chongqing 400039, ChinaSchool of Electronics and Information Engineering, Beihang University, Beijing 100191, ChinaSchool of Electronics and Information Engineering, Beihang University, Beijing 100191, ChinaSouthwest Technology and Engineering Research Institute, Chongqing 400039, ChinaSchool of Electronics and Information Engineering, Beihang University, Beijing 100191, ChinaYunnan Innovation Institute·BUAA, Kunming 650233, ChinaUnmanned Aerial Vehicle (UAV) robot microwave imaging systems have attracted comprehensive attention. Compared with visible light and infrared imaging systems, microwave imaging is not susceptible to weather. Active microwave imaging systems have been realized in UAV robots. However, the scattering signals of geographical objects from satellite transmitting systems received by UAV robots to process imaging is studied rarely, which reduces the need of load weight for the UAV robot. In this paper, a multi-path scattering model of vegetation on the earth surface is proposed, and then the microwave imaging algorithm is introduced to reconstruct the images from the UAV robot receiving the scattering data based on the multi-path model. In image processing, it is assumed that the orbit altitude of a transmitter loaded on the satellite remains unchanged, and the receiver loaded UAV robot obtains the reflective information from ground vegetation with different zenith angles. The imaging results show that the angle change has an impact on the imaging resolution. The combination of electromagnetic scattering model and image processing method contributes to understanding the image results and the multi-path scattering mechanisms of vegetation, which provide a reference for the research and development of microwave imaging systems of UAV robot networking using satellite transmitting signals.https://www.mdpi.com/1424-8220/22/22/8736UAV robot microwave imagingmulti-path scattering modelUAV networking using satellite transmitting signals |
| spellingShingle | Zhihua Chen Xinya Qiao Pei Wu Tiancai Zhang Tao Hong Linquan Fang Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model Sensors UAV robot microwave imaging multi-path scattering model UAV networking using satellite transmitting signals |
| title | Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model |
| title_full | Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model |
| title_fullStr | Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model |
| title_full_unstemmed | Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model |
| title_short | Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model |
| title_sort | unmanned aerial vehicle uav robot microwave imaging based on multi path scattering model |
| topic | UAV robot microwave imaging multi-path scattering model UAV networking using satellite transmitting signals |
| url | https://www.mdpi.com/1424-8220/22/22/8736 |
| work_keys_str_mv | AT zhihuachen unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel AT xinyaqiao unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel AT peiwu unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel AT tiancaizhang unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel AT taohong unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel AT linquanfang unmannedaerialvehicleuavrobotmicrowaveimagingbasedonmultipathscatteringmodel |