Multi-Wave UAV Swarm Defense Under Identity Uncertainty: A Bi-Objective MILP Model
11th International Conference on Recent Advances in Air and Space Technologies, Conference Program, RAST 2026, İstanbul, Türkiye, 13 - 15 Mayıs 2026, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/rast69551.2026.11672605
- Basıldığı Şehir: İstanbul
- Basıldığı Ülke: Türkiye
- Anahtar Kelimeler: counter-UAS, identity uncertainty, mixed-integer linear programming (MILP), multi-objective optimization, pareto optimization, resource allocation, UAV swarm defense, weapon-target assignment
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
This study proposes a bi-objective mixed-integer linear programming (MILP) model that addresses the resource allocation of heterogeneous counter-UAV (C-UAS) defense systems against multi-wave UAV swarm attacks. The model simultaneously minimizes total engagement cost and damage-weighted penetration risk. In order to reflect real operational conditions, the identity uncertainty assumption is adopted, in which the defense system cannot distinguish target identity at the moment of engagement. Real and decoy threats are evaluated under the same engagement rules and the attrition effect of decoy threats on defense resources is modeled indirectly. The model addresses multi-wave threat structure, range-dependent effectiveness, capacity and overflow effects, reload/cooldown constraints, and threat lifecycle within an integrated MILP framework. The bi-objective optimization problem is solved with the ϵ-constraint method to obtain exact Pareto solutions. For large-scale scenarios, the NSGA-II algorithm is used as a complementary approach. The developed model enables quantitative analysis of the effect of low-cost decoy threats on defense systems, contributing to the development of cost-effective defense strategies for decision makers in modern UAV swarm defense problems.