Multipoint primary radar detection association and tracking construction based on BLUE filter

Illegal flights in South America is one of the major problems that aviation authorities must face every day. Illicit aircrafts fly every day over countries and they keep their transponder inactivate to avoid secondary radar location over radar systems. This problem has become a major issue for the commercial aviation and the authorities. In an effort to determine the position of these aircrafts and predict their future movements, the authorities only have a spread and variable primary radar detection point over the radar system. A statistical approach of those data are presented in this paper trying to build a methodology to estimate and associate spread points detected by primary radar with at least two different targets. The parameters used to make that estimation are speed, direction and position. To develop the association of the spread points in a single track and further prediction a Kalman filter and a Best Linear Unbiased Estimator filter are used. Simulations results are presented to demonstrate the effectiveness of the proposed approach. Real time primary radar information is used to test the model.