TY  - JOUR
AU  - Tsiakalos, Anastasios
AU  - Tsiakalos, Apostolos
PY  - 2026
DA  - 2026/09/23
TI  - Wind-Aware Angle-of-Arrival Consistency Validation for Spoofed Guidance Signal Rejection in Unmanned Aerial Vehicles
JO  - ICCK Transactions on Intelligent Systematics
T2  - ICCK Transactions on Intelligent Systematics
JF  - ICCK Transactions on Intelligent Systematics
VL  - 3
IS  - 3
SP  - 186
EP  - 195
DO  - 10.62762/TIS.2026.467986
UR  - https://www.icck.org/article/abs/TIS.2026.467986
KW  - Angle-of-Arrival
KW  - Unmanned Aerial Vehicle
KW  - spoofing detection
KW  - physical-layer security
AB  - Unmanned Aerial Vehicles (UAVs) increasingly rely on wireless guidance and control links which are vulnerable to spoofing and false command injection attacks. Conventional protection mechanisms primarily rely on cryptographic authentication, which may not be sufficient under compromised or replay-based attack scenarios. This paper proposes a physics-informed, wind-aware angle-of-arrival (AoA) consistency validation framework for real-time rejection of spoofed guidance signals. The proposed method exploits geometric consistency between the expected line-of-sight (LOS) direction to a legitimate guidance transmitter and the measured signal bearing at the UAV. The expected bearing is computed from relative positioning and transformed into the UAV body frame using inertial attitude estimates. To mitigate false alarms caused by wind-induced attitude fluctuations, an adaptive stochastic consistency test is introduced, incorporating wind-dependent uncertainty modeling into a Mahalanobis-distance-based hypothesis test. Extensive simulations and trajectory-driven evaluations under varying wind intensities (0–10 m/s), transmitter distances, and adversarial angular offsets demonstrate robust spoofing detection performance. The proposed framework achieves a detection probability numerically evaluated as 1.0000 for angular deviations of 20$^\circ$, while maintaining a false rejection rate of 1.0% under 10 m/s strong gust conditions. The method operates in real time with negligible computational overhead, requiring less than 1 ms per validation cycle, as estimated for typical embedded hardware. The results indicate that wind-aware geometric bearing validation provides an effective secondary integrity layer for UAV guidance systems, enhancing resilience against spoofed control signals without requiring modifications to communication protocols.
SN  - 3068-5079
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Tsiakalos2026WindAware,
  author = {Anastasios Tsiakalos and Apostolos Tsiakalos},
  title = {Wind-Aware Angle-of-Arrival Consistency Validation for Spoofed Guidance Signal Rejection in Unmanned Aerial Vehicles},
  journal = {ICCK Transactions on Intelligent Systematics},
  year = {2026},
  volume = {3},
  number = {3},
  pages = {186-195},
  doi = {10.62762/TIS.2026.467986},
  url = {https://www.icck.org/article/abs/TIS.2026.467986},
  abstract = {Unmanned Aerial Vehicles (UAVs) increasingly rely on wireless guidance and control links which are vulnerable to spoofing and false command injection attacks. Conventional protection mechanisms primarily rely on cryptographic authentication, which may not be sufficient under compromised or replay-based attack scenarios. This paper proposes a physics-informed, wind-aware angle-of-arrival (AoA) consistency validation framework for real-time rejection of spoofed guidance signals. The proposed method exploits geometric consistency between the expected line-of-sight (LOS) direction to a legitimate guidance transmitter and the measured signal bearing at the UAV. The expected bearing is computed from relative positioning and transformed into the UAV body frame using inertial attitude estimates. To mitigate false alarms caused by wind-induced attitude fluctuations, an adaptive stochastic consistency test is introduced, incorporating wind-dependent uncertainty modeling into a Mahalanobis-distance-based hypothesis test. Extensive simulations and trajectory-driven evaluations under varying wind intensities (0–10 m/s), transmitter distances, and adversarial angular offsets demonstrate robust spoofing detection performance. The proposed framework achieves a detection probability numerically evaluated as 1.0000 for angular deviations of 20\$^\circ\$, while maintaining a false rejection rate of 1.0\% under 10 m/s strong gust conditions. The method operates in real time with negligible computational overhead, requiring less than 1 ms per validation cycle, as estimated for typical embedded hardware. The results indicate that wind-aware geometric bearing validation provides an effective secondary integrity layer for UAV guidance systems, enhancing resilience against spoofed control signals without requiring modifications to communication protocols.},
  keywords = {Angle-of-Arrival, Unmanned Aerial Vehicle, spoofing detection, physical-layer security},
  issn = {3068-5079},
  publisher = {Institute of Central Computation and Knowledge}
}