Abstract

With the increasing complexity of information in Beyond Visual Range (BVR) air combat, traditional information indications can only provide support for pilots from the perspective of attack, which is difficult to meet the decision-making requirements in modern air combat. To address these problems, a new concept of tactical control range (TCR) is proposed under the consideration of escape maneuver. Firstly, the corresponding offline simulation model is given and the sample database is established. Then, fitting algorithm based on Sparse Auto Encoder (SAE) network is designed by introducing the deep learning theory. The simulation results show that the SAE network improves the computing accuracy while greatly reducing the computing time. The solution error can be controlled within 150 meters, and the average solution time is only 12ms. TCR can effectively makes up for the lack of information support and provide pilots with more timely decision basis in air combat, which is practical for improving the combat efficiency.

Full Text
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