Multi-Sensor Aircraft Classification

Automatic Dependent Surveillance-Broadcast (ADS-B) is a useful tool to for air traffic controllers, military and other sources that are invested in understanding a national or global air picture. While it is highly available, it can sometimes lack integrity due to hacking, spoofing or, even, unintentional inaccuracies in the broadcast. Unlike primary radar, ADS-B's lack of trustworthiness makes it not feasible to rely on it alone. Fusing other data sources with ADS-B can help confirm the accuracy of the broadcasts or allow ADS-B to act as a surrogate for primary radar and bolster the information that primary radar can provide. This paper presents an effective method of using ADS-B data as a surrogate for primary 3D radar by combining the kinematic information that ADS-B data provides with weather and aircraft images to make predictions about aircraft characteristics.