Predicting the future movement of hostile targets based on artificial neural network on the radar screen

Tavakoli, Mehdi; Farahmand Rad, Mohammad; Balouchestani, Hamid

Predicting the future movement of hostile targets based on artificial neural network on the radar screen

Document Type : Original Article

Authors

Mehdi Tavakoli ¹

Mohammad Farahmand Rad ²

Hamid Balouchestani ³

¹ . Faculty of Electrical Engineering, Khatam Al-Anbia Air Defense University, Tehran, Iran

² Researcher

³ Master's Degree, Electrical Engineering Faculty, Kashan University, Kashan, Iran.

Abstract

As radar technology advances, training operators to effectively analyze and respond to potential threats is critical. This research presents a PPI radar display simulator implemented using C# and WPF platform. This simulator integrates a neural network powered by the Encog library with a radar display to predict attack locations and future trajectories of simulated targets. The implemented neural network has a four-layer architecture that allows operators to adjust multiple network parameters to suit their needs. With the ability to change training data through Excel files, this simulator has increased interaction with the user, and it is also possible to add or remove target locations. This allows for more realistic scenarios. The implemented simulator allows the operators of Khatam al-Anbia Air Defense University to strengthen their skills in radar data analysis and familiarize themselves with a comprehensive and advanced learning environment of new generation radar displays equipped with neural network technology.

Keywords

Encog Library

Neural Network

Prediction

Simulator

Training