Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream

Secondary surveillance radar (SSR) and automatic dependent surveillance-broadcast (ADS-B) are the two main surveillance methods coexisting in the airspace surveillance system. In order to improve the accuracy and stability of surveillance, real-time fusion of SSR and ADS-B trajectory is crucial. In view of the fact that the existing methods are difficult to meet the real-time fusion requirements of large-scale trajectories, a real-time fusion method of SSR and ADS-B data streams was designed with big data technology. This method was based on the big data processing framework of micro-batch processing and followed the MapReduce programming model. While obtaining a fusion trajectory of high quality, it ensured high concurrency and real-time data processing capability of the system. Finally, a real-time flight simulation experiment based on real flight data was carried out to verify the feasibility of the method.