The restraining outlier method of flight paths tracking based on ADS-B system

摘要

Considering the problem that measurement outliers exist in ADS-B monitoring system and seriously affect the stability and accuracy of the Kalman filter, an improved “current” statistical model Kalman filtering algorithm has been proposed in this paper. The algorithm can dynamically adjust the acceleration variance and the maneuvering frequency, automatically identify and eliminate outliers, through a combination of CA model, so as to realize the track forward and reverse extrapolation and smoothing data loss. Simulation results show that the algorithm can not only effectively eliminate outliers and reduce the adverse impact on the filtering accuracy, but also has high tracking accuracy in the weak or the high maneuvering situation.