Скачать или смотреть Micro Doppler based target classification, SIH 2024

The project focuses on developing a radar-based system utilizing micro-Doppler signatures to distinguish between drones and birds. By detecting unique movement patterns such as drone propellers and bird wingbeats, the system enhances airspace surveillance accuracy. Using Frequency Modulated Continuous Wave (FMCW) radar and a Convolutional Neural Network (CNN) model, the solution automates the classification process, reducing false positives. The system leverages micro-Doppler effects, offering more precise detection while maintaining efficiency. It integrates seamlessly into existing radar infrastructure, improving security, reducing operational costs, and minimizing environmental disruptions caused by false alarms.