Neutralization of intruder uav systems by a team of rotary-wing platforms
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Abstract (EN)
The rapid development and widespread adoption of drone technology has led to the emergence of new threat scenarios, particularly in modern battlefields. The use of low-cost and easily accessible drones in coordinated swarms poses significant challenges for existing air defense systems. Developing effective solutions against such threats has become a critical necessity. This thesis proposes a counter-drone swarm system designed to neutralize enemy drone swarms through kinetic methods. The proposed system consists of three main phases. In the first phase, interceptor drones move toward the target area in a coordinated manner using consensus-based formation control. In the second phase, as the interceptor swarm approaches the target drone swarm, the distribution of target drones is analyzed using the K-means clustering algorithm, and the interceptor swarm divides into an optimal number of sub-groups to assume the most advantageous positions for engagement. In the third phase, target assignment is performed using the Greedy algorithm, and each interceptor drone is guided to its assigned target using Kalman filter-based state estimation and Proportional Navigation guidance. The system performance was modeled and simulated in MATLAB using drone dynamics in scenarios involving six interceptor drones against six target drones. Comprehensive Monte Carlo simulations were conducted to demonstrate the effectiveness of the proposed sub-group division strategy. In these simulations, two scenarios were tested in parallel at different target distribution widths: one with the sub-grouping strategy enabled and one with it disabled.Simulation results demonstrated that the sub-group division strategy provides significant advantages compared to the direct engagement approach. Across all tested scenarios, the sub-grouping strategy showed substantial reductions in energy consumption, improvements in interception times, optimization in engagement geometry, and decreased the chances of collisions within the interceptor swarm during engagement.
Author
Egemen Türkgenci
Institution
TOBB Economics and Technology University
Elektrik Elektronik Mühendisliği Bilim Dalı
How to Cite
Egemen Türkgenci (Master Thesis). Neutralization of intruder uav systems by a team of rotary-wing platforms, 2025, TOBB Economics and Technology University.
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