A 2D multilateration algorithm used for air traffic localization and tracking

Space capacity and safety of Airspace Surveillance Systems are regularly increasing to meet the demands of air traffic control. Researchers are interested in many directions like optimal sensors deployment, localization and tracking algorithms. Thus, a 2-D Multilateration algorithm is proposed to accurately identify the aircraft position. It is based on the classical Two Ray propagation model. Important parameters that affect the final aircraft estimation position are presented like the path gain factor (interference factor) which is a function of the divergence factor, reflection coefficient and the path difference between the direct and ground reflected rays. The proposed algorithm uses the geographic coordinates (Latitude and Longitude) which are considered more practically used in navigation than Cartesian coordinates that are used in previous algorithms in literature. Hence, General expressions for both the latitude and longitude will be deduced. In order to simulate the algorithm, the Multilateration network at Cairo International Airport is considered to be a pilot area and the results are presented. The results of the proposed algorithm are applied to Kalman filter to achieve aircraft continuous tracking. Finally, the path gain factor effect on tracking capability is discussed.