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. In BVR air combat, engagement decision refers to the choice of the moment the pilot engages a target by assuming an offensive stance and executing corresponding maneuvers. To model this decision, we use the Brazilian Air Force's Aerospace Simulation Environment (\textit{Ambiente de Simula\c{c}\~ao Aeroespacial - ASA} in Portuguese), which generated 3,729 constructive simulations lasting 12 minutes each and a total of 10,316 engagements. We analyzed all samples by an operational metric called the DCA index, which represents, based on the experience of subject matter experts, the degree of success in this type of mission. This metric considers the distances of the aircraft of the same team and the opposite team, the point of Combat Air Patrol, and the number of missiles used. By defining the engagement status right before it starts and the average of the DCA index throughout the engagement, we create a supervised learning model to determine the quality of a new engagement. An algorithm based on decision trees, working with the XGBoost library, provides a regression model to predict the DCA index with a coefficient of determination close to 0.8 and a Root Mean Square Error of 0.05 that can furnish parameters to the BVR pilot to decide whether or not to engage. Thus, using data obtained through simulations, this work contributes by building a decision support system based on machine learning for BVR air combat.
翻译:这项工作的目的是在防御性反空(DCA)飞行任务中为超越视觉范围(BVR)的空中战斗提供一个接触决定支持工具。在BVR的空中战斗中,接触决定指的是通过采取进攻姿态和执行相应动作来选择试点目标的时刻。为模拟这一决定,我们使用了巴西空军的航空航天模拟环境(葡萄牙的\ textit{Ambient de Simula\c}c ⁇ ao Aerospacial - ASA}),它产生了3 729个建设性模拟,每次持续12分钟,共10 316项任务。我们用一个称为DCA指数的业务指标来分析所有样本,该指数代表了实验实验通过采取进攻性姿态和实施相应的动作。我们使用了巴西空军的飞机和对面的飞行模拟环境的距离,战斗空中巡逻点,以及导弹的数量。通过在开始之前立即界定参与状态,以及整个接触过程中DCA指数的平均值,我们创建了一个监督的学习模型,用以确定新的接触的模型质量。根据主题专家的经验,该指数代表了这类飞行任务的成功程度。 一种基于B决定的算法,从B的航空飞行的算算算到B的实验室,可以进行一个基于B的实验室的实验室的实验室的实验室的实验室的实验室的实验室的实验室的算算法,可以进行接近的模型,可以进行一个B级的逻辑到B级的逻辑到B的实验室的逻辑到B的实验室的实验室的实验室的实验室的计算。