Aircraft Detection and State Estimation

Unidentified flying objects can be aircraft that do not continuously broadcast ADS-B. They pose a risk for air traffic safety, territorial violation, espionage, etc. In this study, we introduce a method for detecting and estimating the state of aircraft in Sentinel-2 multispectral satellite images. We construct a dataset of 579 ADS-B annotated aircraft from 69 Sentinel-2 images. A CNN is trained on the dataset to estimate the aircraft state vector i.e. position, velocity, heading, altitude. This work allows real-time monitoring of flying objects in satellite images.