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

Abstract

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 (σ ¯) of −17.62 dBsm for scenario A, and a mean RCS value (σ ¯) 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.

Comprehensive Review: Effectiveness of MIMO and Beamforming Technologies in Detecting Low RCS UAVs

“…Despite their larger size, fixed-wing UAVs often have lower RCS due to their aerodynamically efficient or smooth designs, unlike rotary-wing UAVs such as quadcopters, hexacopters, or octocopters, which have higher RCS due to complex rotor blade designs producing distinctive Doppler signatures, as illustrated in Figure 1. The authors in [13] explain that the variety of UAV designs, from simple toys to advanced fixed-wing and rotarywing types, makes radar detection more difficult. This variety forces radar systems to constantly improve and adopt new methods and technology for better UAV detection and classification.…”

Securing Your Airspace: Detection of Drones Trespassing Protected Areas

“…These capabilities have elevated radar technologies as one of the best candidates for drone detection systems [53][54][55][56][57][58][59]. Evaluating the feasibility of using radar for UAV detection has received considerable attention [41,[60][61][62][63][64][65][66]. However, there are some practical limitations and cost considerations when designing and deploying a radar suitable for detecting drones.…”

PFFNET: A Fast Progressive Feature Fusion Network for Detecting Drones in Infrared Images

“…Various types of small unmanned aerial vehicles threaten infrastructure, hardware and people seriously [1,2]. At the same time, the accurate detection of drone targets in low-resolution, visually blurred infrared images is a challenging task.…”