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Found 4 papers, 2 papers with code
Real-Time Surface-to-Air Missile Engagement Zone Prediction Using Simulation and Machine Learning
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems.
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations
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.
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range.
Engagement Decision Support for Beyond Visual Range Air Combat
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.
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