Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System
Various types of small drones constitute a modern threat for infrastructure and hardware, as well as for humans; thus, special-purpose radar has been developed in the last years in order to identify such drones. When studying the radar signatures, we observed that the majority of the scientific stud...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/7/1/39 |
| _version_ | 1797443605768437760 |
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| author | Ioannis K. Kapoulas Antonios Hatziefremidis A. K. Baldoukas Evangelos S. Valamontes J. C. Statharas |
| author_facet | Ioannis K. Kapoulas Antonios Hatziefremidis A. K. Baldoukas Evangelos S. Valamontes J. C. Statharas |
| author_sort | Ioannis K. Kapoulas |
| collection | DOAJ |
| description | Various types of small drones constitute a modern threat for infrastructure and hardware, as well as for humans; thus, special-purpose radar has been developed in the last years in order to identify such drones. When studying the radar signatures, we observed that the majority of the scientific studies refer to multirotor aerial vehicles; there is a significant gap regarding small, fixed-wing Unmanned Aerial Vehicles (UAVs). Driven by the security principle, we conducted a series of Radar Cross Section (RCS) simulations on the Euclid fixed-wing UAV, which has a wingspan of 2 m and is being developed by our University. The purpose of this study is to partially fill the gap that exists regarding the RCS signatures and identification distances of fixed-wing UAVs of the same wingspan as the Euclid. The software used for the simulations was POFACETS (v.4.1). Two different scenarios were carried out. In scenario A, the RCS of the Euclid fixed-wing UAV, with a 2 m wingspan, was analytically studied. Robin radar systems’ Elvira Anti Drone System is the simulated radar, operating at 8.7 to 9.65 GHz; θ angle is set at 85° for this scenario. Scenario B studies the Euclid RCS within the broader 3 to 16 Ghz spectrum at the same θ = 85° angle. The results indicated that the Euclid UAV presents a mean RCS value <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>(</mo><mrow><mover accent="true"><mrow><mi>σ</mi><mo> </mo></mrow><mo stretchy="true">¯</mo></mover></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> of −17.62 dBsm for scenario A, and a mean RCS value <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>(</mo><mrow><mover accent="true"><mrow><mi>σ</mi><mo> </mo></mrow><mo stretchy="true">¯</mo></mover></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> of −22.77 dBsm for scenario B. These values are much smaller than the values of a typical commercial quadcopter, such as DJI Inspire 1, which presents −9.75 dBsm and −13.92 dBsm for the same exact scenarios, respectively. As calculated in the study, the Euclid UAV can penetrate up to a distance of 1784 m close to the Elvira Anti Drone System, while the DJI Inspire 1 will be detected at 2768 m. This finding is of great importance, as the obviously larger fixed-wing Euclid UAV will be detected about one kilometer closer to the anti-drone system. |
| first_indexed | 2024-03-09T12:59:29Z |
| format | Article |
| id | doaj.art-184894b4b4794b04ab11e8f40a2da811 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-09T12:59:29Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-184894b4b4794b04ab11e8f40a2da8112023-11-30T21:55:26ZengMDPI AGDrones2504-446X2023-01-01713910.3390/drones7010039Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone SystemIoannis K. Kapoulas0Antonios Hatziefremidis1A. K. Baldoukas2Evangelos S. Valamontes3J. C. Statharas4General Department, National and Kapodistrian University of Athens, GR 34400 Psachna, GreeceDepartment of Aerospace Science and Technology, National and Kapodistrian University of Athens, GR 34400 Psachna, GreeceGeneral Department, National and Kapodistrian University of Athens, GR 34400 Psachna, GreeceDepartment of Electrical and Electronics Engineering, University of West Attica, GR 12241 Athens, GreeceGeneral Department, National and Kapodistrian University of Athens, GR 34400 Psachna, GreeceVarious types of small drones constitute a modern threat for infrastructure and hardware, as well as for humans; thus, special-purpose radar has been developed in the last years in order to identify such drones. When studying the radar signatures, we observed that the majority of the scientific studies refer to multirotor aerial vehicles; there is a significant gap regarding small, fixed-wing Unmanned Aerial Vehicles (UAVs). Driven by the security principle, we conducted a series of Radar Cross Section (RCS) simulations on the Euclid fixed-wing UAV, which has a wingspan of 2 m and is being developed by our University. The purpose of this study is to partially fill the gap that exists regarding the RCS signatures and identification distances of fixed-wing UAVs of the same wingspan as the Euclid. The software used for the simulations was POFACETS (v.4.1). Two different scenarios were carried out. In scenario A, the RCS of the Euclid fixed-wing UAV, with a 2 m wingspan, was analytically studied. Robin radar systems’ Elvira Anti Drone System is the simulated radar, operating at 8.7 to 9.65 GHz; θ angle is set at 85° for this scenario. Scenario B studies the Euclid RCS within the broader 3 to 16 Ghz spectrum at the same θ = 85° angle. The results indicated that the Euclid UAV presents a mean RCS value <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>(</mo><mrow><mover accent="true"><mrow><mi>σ</mi><mo> </mo></mrow><mo stretchy="true">¯</mo></mover></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> of −17.62 dBsm for scenario A, and a mean RCS value <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mo>(</mo><mrow><mover accent="true"><mrow><mi>σ</mi><mo> </mo></mrow><mo stretchy="true">¯</mo></mover></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> of −22.77 dBsm for scenario B. These values are much smaller than the values of a typical commercial quadcopter, such as DJI Inspire 1, which presents −9.75 dBsm and −13.92 dBsm for the same exact scenarios, respectively. As calculated in the study, the Euclid UAV can penetrate up to a distance of 1784 m close to the Elvira Anti Drone System, while the DJI Inspire 1 will be detected at 2768 m. This finding is of great importance, as the obviously larger fixed-wing Euclid UAV will be detected about one kilometer closer to the anti-drone system.https://www.mdpi.com/2504-446X/7/1/39radar cross sectionfixed wingsmall wingspandetectionclassification |
| spellingShingle | Ioannis K. Kapoulas Antonios Hatziefremidis A. K. Baldoukas Evangelos S. Valamontes J. C. Statharas Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System Drones radar cross section fixed wing small wingspan detection classification |
| title | Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System |
| title_full | Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System |
| title_fullStr | Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System |
| title_full_unstemmed | Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System |
| title_short | Small Fixed-Wing UAV Radar Cross-Section Signature Investigation and Detection and Classification of Distance Estimation Using Realistic Parameters of a Commercial Anti-Drone System |
| title_sort | small fixed wing uav radar cross section signature investigation and detection and classification of distance estimation using realistic parameters of a commercial anti drone system |
| topic | radar cross section fixed wing small wingspan detection classification |
| url | https://www.mdpi.com/2504-446X/7/1/39 |
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