Calculation of the Combined Threat of Air Targets Using Neuro-Fuzzy Systems

Document Type : Original Article

Authors

1 Lecturer, Khatam Al-Anbia University of Air Defense, Tehran, Iran

2 Assistant Professor, Khatam Al-Anbia University of Air Defense, Tehran, Iran

Abstract

In recent years, intelligent structures play the key role in different military fields and take the place of human operators in novel armed services step by step. Threat evaluation of flying air targets in command and control systems is performed by expert operators through their knowledge and experience. Analysis of input data in the data-fusion systems is a very difficult task requiring complicated decision. Capability and accuracy of intelligent systems for threat prediction of flying air targets base on different received parameters can be a great assist in final macking decision. In this study, a neural network and ANFIS regression models are used to determine the priority of the threat of flying air targets in the command and control systems intelligently and instantly. The error of trained neural network and ANFIS for test dataset are 4.14% and 1.65%, respectively indicating superior ability of these structures in threat estimation of flying air targets. Furthermore, relationships among target variables and threat level is studied. Finally, a dynamic battle scene with different flying air targets is simulated and developed moled is validated.

Keywords

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References

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Radar
Volume 9, Issue 2 - Serial Number 26
November 2022
Pages 69-78

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History

  • Receive Date: 08 November 2021
  • Revise Date: 10 October 2022
  • Accept Date: 16 October 2022
  • Publish Date: 22 November 2022

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