Abstract

Aiming at the maneuvering decision of aircraft in air combat, an intelligent maneuvering decision model based on convolutional neural network(CNN) is proposed in this paper. Firstly, the situation data, maneuvering decision variables and evaluation indexs are given, and a CNN model that can realize intelligent maneuvering decision is established. Then, according to the evaluation indexes, the structure and parameters of the CNN model are adjusted through the simulation experiments to improve the accuracy and robustness of the maneuvering decision. After that, the validity of the intelligent maneuvering decision model proposed in this paper is verified through comparative experiments that the CNN model can make stable maneuvering decisions with high accuracy. Finally, the flight path in an air combat process is presented.

Highlights

  • Future air war will inevitably develop towards unmanned and autonomous[1]

  • In the one-to-one air combat, an air combat process was set up as a simulation, and the situation information of both sides was recorded in simulation

  • The situation information of both sides collected in the air combat are as follows

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Summary

Introduction

Autonomous maneuver decision is a critical part to reach a higher level of autonomy and air-combat decision[2, 3]. Literature[1] realized the maneuvering decision through monte carlo reinforcement learning and showed the flight path and the variation of control variables, which proved the validity of the method. This literature only used the position and attitude of both sides to describe the air combat state. In order to realize the intelligent aircraft maneuvering decision, this paper constructs a model using CNN to fit maneuvering decision variables. The maneuvering decision model takes more comprehensive factors as inputs and directly outputs the change rate of attack angle and the change rate of throttle coefficient, making the decision results more accurate and intuitive

Convolutional Neural Network
Framework of the Maneuvering Decision System
Data Preprocessing
Model Training
Mean square error
Goodness of fitting
Datesets
The situation information of our side
Training and Testing
The Flight Path of an Air Combat
Conclusion
Full Text
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