Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry
The increase in drone misuse by civilian apart from military applications is alarming and need to be addressed. This drone is characterized as a low altitude, slow speed, and small radar cross-section (RCS) (LSS) target and is considered difficult to be detected and classified among other biological...
| Published in: | Sensors |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/15/3332 |
| _version_ | 1852737023552520192 |
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| author | Surajo Alhaji Musa Raja Syamsul Azmir Raja Abdullah Aduwati Sali Alyani Ismail Nur Emileen Abdul Rashid |
| author_facet | Surajo Alhaji Musa Raja Syamsul Azmir Raja Abdullah Aduwati Sali Alyani Ismail Nur Emileen Abdul Rashid |
| author_sort | Surajo Alhaji Musa |
| collection | DOAJ |
| container_title | Sensors |
| description | The increase in drone misuse by civilian apart from military applications is alarming and need to be addressed. This drone is characterized as a low altitude, slow speed, and small radar cross-section (RCS) (LSS) target and is considered difficult to be detected and classified among other biological targets, such as insects and birds existing in the same surveillance volume. Although several attempts reported the successful drone detection on radio frequency-based (RF), thermal, acoustic, video imaging, and other non-technical methods, however, there are also many limitations. Thus, this paper investigated a micro-Doppler analysis from drone rotating blades for detection in a special Forward Scattering Radar (FSR) geometry. The paper leveraged the identified benefits of FSR mode over conventional radars, such as improved radar cross-section (RCS) value irrespective of radar absorbing material (RAM), direct signal perturbation, and high resolutions. To prove the concept, a received signal model for micro-Doppler analysis, a simulation work, and experimental validation are elaborated and explained in the paper. Two rotating blades aspect angle scenarios were considered, which are (i) when drone makes a turn, the blade cross-sectional area faces the receiver and (ii) when drone maneuvers normally, the cross-sectional blade faces up. The FSR system successfully detected a commercial drone and extracted the micro features of a rotating blade. It further verified the feasibility of using a parabolic dish antenna as a receiver in FSR geometry; this marked an appreciable achievement towards the FSR system performance, which in future could be implemented as either active or passive FSR system. |
| format | Article |
| id | doaj-art-9a92902b8dae408d8bf6df4497bbac2f |
| institution | Directory of Open Access Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-9a92902b8dae408d8bf6df4497bbac2f2025-08-19T21:06:17ZengMDPI AGSensors1424-82202019-07-011915333210.3390/s19153332s19153332Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar GeometrySurajo Alhaji Musa0Raja Syamsul Azmir Raja Abdullah1Aduwati Sali2Alyani Ismail3Nur Emileen Abdul Rashid4Wireless and Photonics Networks (WIPNET), Department of Computer and Communication System Engineering University Putra Malaysia (UPM), Serdang 43400, Selangor Darul Ehsan, MalaysiaWireless and Photonics Networks (WIPNET), Department of Computer and Communication System Engineering University Putra Malaysia (UPM), Serdang 43400, Selangor Darul Ehsan, MalaysiaWireless and Photonics Networks (WIPNET), Department of Computer and Communication System Engineering University Putra Malaysia (UPM), Serdang 43400, Selangor Darul Ehsan, MalaysiaWireless and Photonics Networks (WIPNET), Department of Computer and Communication System Engineering University Putra Malaysia (UPM), Serdang 43400, Selangor Darul Ehsan, MalaysiaFaculty of Electrical Engineering, University Teknologi Mara, Shah Alam 40450, Selangor, MalaysiaThe increase in drone misuse by civilian apart from military applications is alarming and need to be addressed. This drone is characterized as a low altitude, slow speed, and small radar cross-section (RCS) (LSS) target and is considered difficult to be detected and classified among other biological targets, such as insects and birds existing in the same surveillance volume. Although several attempts reported the successful drone detection on radio frequency-based (RF), thermal, acoustic, video imaging, and other non-technical methods, however, there are also many limitations. Thus, this paper investigated a micro-Doppler analysis from drone rotating blades for detection in a special Forward Scattering Radar (FSR) geometry. The paper leveraged the identified benefits of FSR mode over conventional radars, such as improved radar cross-section (RCS) value irrespective of radar absorbing material (RAM), direct signal perturbation, and high resolutions. To prove the concept, a received signal model for micro-Doppler analysis, a simulation work, and experimental validation are elaborated and explained in the paper. Two rotating blades aspect angle scenarios were considered, which are (i) when drone makes a turn, the blade cross-sectional area faces the receiver and (ii) when drone maneuvers normally, the cross-sectional blade faces up. The FSR system successfully detected a commercial drone and extracted the micro features of a rotating blade. It further verified the feasibility of using a parabolic dish antenna as a receiver in FSR geometry; this marked an appreciable achievement towards the FSR system performance, which in future could be implemented as either active or passive FSR system.https://www.mdpi.com/1424-8220/19/15/3332micro Dopplerforward scatter radar (FSR)Low-Slow-Small (LSS) target detection |
| spellingShingle | Surajo Alhaji Musa Raja Syamsul Azmir Raja Abdullah Aduwati Sali Alyani Ismail Nur Emileen Abdul Rashid Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry micro Doppler forward scatter radar (FSR) Low-Slow-Small (LSS) target detection |
| title | Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry |
| title_full | Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry |
| title_fullStr | Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry |
| title_full_unstemmed | Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry |
| title_short | Low-Slow-Small (LSS) Target Detection Based on Micro Doppler Analysis in Forward Scattering Radar Geometry |
| title_sort | low slow small lss target detection based on micro doppler analysis in forward scattering radar geometry |
| topic | micro Doppler forward scatter radar (FSR) Low-Slow-Small (LSS) target detection |
| url | https://www.mdpi.com/1424-8220/19/15/3332 |
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