![]() Auto ACAS is not a pilot advisory system or a de-confliction system rather, Auto ACAS performs an automatic, aggressive maneuver to avoid collisions with other aircraft and returns control to the pilot as soon as the collision is prevented. TACM should be particularly useful for evaluation of G-protective equipment and maneuvers, as well as fighter aircrew medical evaluations. placed on providing protection for aircraft performing air combat maneuvers while eliminating nuisance. TACM captures the high onset, high amplitude +Gz changes of aerial combat when G-LOC and blackouts are more likely to occur. TACM simulates the seesaw pattern of +Gz forces of aerial combat and retains the reproducibility needed for acceleration research and evaluation. TACM accounted for all four incidents of G-Induced Loss of Consciousness (G-LOC) and most incidents of blackouts (5 of 8) observed. There were 15 centrifuge subjects used in this study. However, how to use a large amount of trajectory data generated by air combat confrontation training to achieve real-time and accurate prediction of target maneuver trajectory is an urgent problem to be solved. TACM was compared against the widely accepted 4.5-7G and 5-9G SACMs. Target maneuver trajectory prediction is an important prerequisite for air combat situation awareness and maneuver decision-making. You have just seen glimpses of the air war in. TACM consists of 9G x 5 s, 5G x 1 s, 8G x 5 s, and 4G x 2 s. Meeting these weapons-firing requirements must, therefore, be the goal of all fighter tactics and maneuvering. ![]() Differential game of pursuit and evasion was. Then, considering the different state transition effects of various actions. Firstly, the UCAV flight maneuver model and maneuver library of both opposing sides are established. This article describes a simulated aerial combat maneuver (SACM) named the Tactical Aerial Combat Maneuver (TACM).Ī more representative centrifuge-based SACM can be devised for high-G acceleration research and evaluation. Differential game theory is a typical representative air combat maneuver decision method based on game theory. To solve the maneuvering decision problem in air combat of unmanned combat aircraft vehicles (UCAVs), in this paper, an autonomous maneuver decision method is proposed for a UCAV based on deep reinforcement learning. There is a need for a more operationally relevant +Gz profile for centrifuge-based research and evaluation.
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