| Proj No. | A3021-251 |
| Title | Next-Generation Intelligent Sensing based on the AI-Enhanced Existing Experiment Platform |
| Summary | This project aims to address the technical limitation of traditional radar systems in detecting agile and dynamic targets within complex scenarios. Students will use FMCW (Frequency-Modulated Continuous-Wave) radar or pulsed-Doppler radar systems to detect the target such as UAVs. They can use the high-performance digital signal processing (DSP) boards (already have) and associated software (MATLAB or Python) for echo signal analysis. They can use machine learning models, such as decision trees, support vector machines (SVM), and ensemble methods to detect the UAVs. Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks may also be helpful. Gain hands-on experience with cutting-edge AI and radar technologies. Work in a collaborative research environment with access to advanced facilities. Contribute to significant research with potential applications in security and defense. Collaborate with experts in the field and participate in academic publications. This FYP course offers a comprehensive and detailed exploration of AI-enhanced UAV detection using advanced radar technologies, providing students with the skills and experience needed to excel in this innovative research area. We are looking for motivated and talented students to join our team and make substantial contributions to this project. |
| Supervisor | A/P Chau Yuen (Loc:S1 > S1 B1A > S1 B1A 12, Ext: +65 67905420) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Connected Smart Mobility Lab (COSMO) (Loc: S2-B3b-10) |
| Single/Group: | Single |
| Area: | Wireless and Communications Engineering |
| ISP/RI/SMP/SCP?: |