Multiple Radar

Multiple radar systems integrate data from several radar units to enhance accuracy and robustness compared to single-radar approaches. Current research focuses on improving object detection and tracking through advanced signal processing techniques, including the application of machine learning models like convolutional neural networks and Kalman filters, and the development of novel algorithms such as distributed auctions for decentralized coordination. These advancements are significantly impacting fields like autonomous driving, weather forecasting (particularly tornado prediction and convective initiation nowcasting), and satellite tracking, where improved accuracy and reliability are crucial for safety and operational efficiency.