A new nonlinear smooth variable structure filter algorithm applied to air traffic control tracking
Zhen Shi, Shuai Chen, Jicheng Ding · 2016
A target-tracking problem based on Air Traffic Control (ATC) Scenario is a typical estimation problem. The target-tracking process that provides good estimation accuracy and robustness to disturbances is often quite important. In order to refine the target-tracking performance, a new nonlinear smooth variable structure filter algorithm is proposed to handle the ATC tracking problem with erroneous measurements. The new estimation algorithm is developed from a fifth-degree cubature Kalman filter, smooth variable structure filter and a time-varying boundary layer. The whole estimation process mainly relies on acquisition of the cubature point, the gain matrices and the time-varying boundary layer rather than updating the error covariance matrix. Simulation results show that the correctness and efficacy of the new algorithm used in the ATC tracking process is superior to other estimation methods. Moreover, the new algorithm provides an alternative fault detection function for the estimation process.