Radar systems have been integral to airspace surveillance and civil aviation monitoring since its early widespread application during WWII. However, the discrimi- nation between friendly and hostile aircrafts has always been challenging due to the limited amount of information that can be obtained from an aircraft in the critical decision-making timeframe. In this paper, an AI machine learning technique is applied for aircraft echoes classification and decision making with significant results in accuracy and recall.

Multi-Input 2D Convolutional Neural Network for Radar Target Identification

D'angelo T.;Danesi M.;Zich E. L.;Martinez G. F.;Zich Riccardo
2025-01-01

Abstract

Radar systems have been integral to airspace surveillance and civil aviation monitoring since its early widespread application during WWII. However, the discrimi- nation between friendly and hostile aircrafts has always been challenging due to the limited amount of information that can be obtained from an aircraft in the critical decision-making timeframe. In this paper, an AI machine learning technique is applied for aircraft echoes classification and decision making with significant results in accuracy and recall.
2025
Multi-Input 2D Convolutional Neural Network for Radar Target Identification
Radar, convolutional neural networks, object detection, continuous wavelet transforms.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1305225
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