Estimation fusion with radar and ADS-B for air traffic surveillance

The surveillance sensor that has been mainly used for target tracking in air traffic control (ATC) environment is radar. The automatic dependent surveillance - broadcasting (ADS-B), which is based on the technologies of global navigation satellite systems (GNSS), is recently participating in ATC systems for more accurate and reliable surveillance. Although ADS-B provides more accurate and a wider variety of measurements than does radar, it needs careful considerations for the application of the ATC systems. This is due to the fact that the reliability of ADS-B measurements is dependent upon each aircraft whereas that of radar is not. This study proposes a practical system for the estimation fusion of multiple heterogeneous sensors, which includes radar and ADS-B, whose measurements and sensor characteristics are different from one another. A centralized fusion architecture for the data that are received asynchronously from multiple sensors is adopted for the optimum estimation fusion. The three-dimensional earth-centered earth-fixed (ECEF) coordinate system is used for the common coordinates for preprocessing and filtering in order to avoid the registration errors, which can occur in two-dimensional coordinates with a stereographic projection at the system center. In case of the ADS-B, the validity of the sensor data for each aircraft is primarily checked using the accuracy and integrity information of the aircraft. Another important validation for the ADS-B is performed using a comparison of the ADS-B data with the radar data because the ADS-B validation information from each aircraft may not be fully reliable. Furthermore, additional measurements from the downlinked aircraft parameters (DAP), which are available in mode-S radar and ADS-B, are incorporated into state estimation. A variable-sized measurement vector and matrix are used for the tracking filter in order to dynamically reflect the availability of the additional measurements. The simulation results indi- ate that the proposed fusion system can improve the tracking performance with the advantages of different types of surveillance sensors.