Joint UAV Trajectory Planning and ISAC Beamforming via Hierarchical Optimization
IEEE Transactions on Vehicular Technology, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1109/tvt.2026.3734502
- Dergi Adı: IEEE Transactions on Vehicular Technology
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Compendex, INSPEC, Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Anahtar Kelimeler: beam forming, Cramér-Rao bound, Integrated sensing and communication (ISAC), trajectory optimization, unmanned aerial vehicle (UAV)
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) systems are promising for search-and-rescue applications. A UAV platform can simultaneously track moving targets while supporting high-speed data transmission. However, such systems face significant challenges due to their coupled objectives, involving two interdependent processes: beamforming for balancing sensing and communication performance, and trajectory planning from a global perspective to ensure efficient and stable search operations. Both tasks lead to non-convex optimization problems with high computational complexity. To address these challenges, we propose a stage-wise closed-loop architecture with periodic Model Predictive Control (MPC) replanning and slot-level precoding. At each replanning stage, the trajectory module integrates the orienteering problem (OP) for waypoint selection and sequential convex programming (SCP) for finite-horizon refinement, while the precoding module reconstructs the position-dependent channels and applies iterative weighted regularized zero-forcing together with null-space projection at the active slots. Numerical results demonstrate that the proposed approach effectively enables trajectory planning while balancing sensing and communication objectives in UAV assisted ISAC systems. It reduces computational complexity, achieves high tracking accuracy, and maintains communication quality of service comparable to baseline schemes.