Multi-sensor data fusion based on environment database for airport surface surveillance

The ADS-B (Automatic Dependent Surveillance - Broadcast) and MLAT (Multilateration) are becoming the leading surveillance techniques in the field of ATC (Air Traffic Control), and will play important roles in the future´s tracking system. It is inevitable to need a framework to fuse the data from these modern techniques. However, traditional fusion method dose not provide sufficient precision in the surface surveillance and easily brings out saw-shaped trajectory. This paper designs a hybrid fusion framework based on environment database. The hybrid framework includes centralized filters and distributed filters to deal with the relations among different sensors. The environment database is used to better the settings of adaptive IMM in each sensor. Under such framework, ADS-B and MLAT data are processed intensively to achieve high accuracy. Experiment results based on simulation and practical data illustrate the algorithm can achieve high precision.