Multi-Sensor Fusion for UAV Classification Based on Feature Maps of Image and Radar Data
Researchers have developed a new methodology for classifying unmanned aerial vehicles (UAVs) by fusing multi-sensor data into a Deep Neural Network (DNN). This DNN model integrates high-level features extracted from thermal, optronic, and radar data. The architecture specifically utilizes a Convolutional Neural Network (CNN) to combine these features, aiming to achieve higher classification accuracy than using individual sensors alone. AI