This paper proposes a system for autonomous aerial combat of next generation unmanned combat aerial vehicles(UVACs). The system includes a decision making scheme, positional prediction of targets, an aircraft model analysis, and a basic fighter maneuvering (BFM)-based combat guidance law designed to generate effective combat maneuvers. A oneon-one combat simulation environment is set up, and the virtual fighter pilot (VFP) combat simulation results are addressed. The VFP proposed in this paper follows the mindset of an real human pilot, and all the subcomponents that reflect the thought processes are modularized. The designed BFM-based aerial combat guidance law conducts suboptimal combat maneuvers in real time. In order for a fighter jet to attain advantageous positions in aerial combat, it must have the ability to carry out high agility maneuvers. Therefore, a V-n diagram and an energy-maneuverability chart analysis are used to determine the limits of the aircraft’s flight operable regions and to find the corner velocity of the aircraft model for the maximum rate of turn. Based on the measured combat geometry, the VFP carries out decision making processes and assesses situations in terms of scoring functions. In order to preoccupy advantageous geometry in combat, the system estimates the future positions of the target using velocity estimation-based target prediction. The modularized VFP is designed using a MATLAB/Simulink, and its simulation environment is designed based on an F-16 model. The performance of the designed VFP is verified, and through animation, the maneuvers of the UCAVs are visualized in real time.

/pdf/design-of-a-virtual-fighter-pilot-and-simulation-environment-3v9z597sgr.pdf

Design of a Virtual Fighter Pilot and Simulation Environment for Unmanned Combat Aerial Vehicles

This paper describes research performed in pursuit of autonomous swarm tactics for unmanned aerial vehicles (UAVs) as part of an internally funded effort at the Georgia Tech Research Institute (GTRI). Human engineered swarming tactics, reinforcement learned tactics, and aggressive flight maneuvers are explored. Aggressive flight maneuvers included autonomous descents, rolls, and an Immelmann maneuver. These efforts expand on preliminary control capabilities and are intended to enable groups of UAVs to act as a defensive swarm to counter aggressor swarms. All tactics have been validated in simulation using the GTRI-developed SCRIMMAGE [1], [2] simulation engine and were further proven in live-fly experiments throughout the duration of the ACTION effort, which ran from 2017-2019.

Aerial Combat Tactics In Overwhelming Numbers

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Aerial Combat Tactics In Overwhelming Numbers