1 code implementation • 5 Mar 2024 • Jay Patrikar, Joao Dantas, Brady Moon, Milad Hamidi, Sourish Ghosh, Nikhil Keetha, Ian Higgins, Atharva Chandak, Takashi Yoneyama, Sebastian Scherer
In total, TartanAviation provides 3. 1M images, 3374 hours of Air Traffic Control speech data, and 661 days of ADS-B trajectory data.
1 code implementation • 20 Nov 2023 • Joao P. A. Dantas, Diego Geraldo, Felipe L. L. Medeiros, Marcos R. O. A. Maximo, Takashi Yoneyama
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems.
no code implementations • 19 Apr 2023 • Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama
This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment.
1 code implementation • 9 Jul 2022 • Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air combat.
1 code implementation • 3 Dec 2021 • Joao P. A. Dantas, Andre N. Costa, Marcos R. O. A. Maximo, Takashi Yoneyama
Besides, we employed hyperparameter tuning to identify the most critical features in the algorithm.
no code implementations • 4 Nov 2021 • Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work aims to provide an engagement decision support tool for Beyond Visual Range (BVR) air combat in the context of Defensive Counter Air (DCA) missions.
no code implementations • 4 Nov 2021 • Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range.