In order to solve the problem that the maneuvering target tracking performance of the"current"statistical model is degraded in complex airport environment due to fixed maneuvering frequency and assumed acceleration limit value,a bivariate adaptive"current"statistical model filtering algorithm is proposed.Initially,the maneuvering frequency of real-time online adjustment is calculated by using the first-order time dependent process model of acceleration noise.Then,according to the position state estimation value and the acceleration change rate,the acceleration variance of real-time online update is derived through the kinematics theoretical model and the position filtering residual,which theoretically realizes the adaptive update of the model.Finally,based on the real automatic dependent surveillance-broadcast(ADS-B)trajectory data of the scene,the verification results show that the improved"current"statistical model can achieve adaptive parameter adjustment on the basis of unequal interval prediction,and the trajectory fitting accuracies in position,velocity,and acceleration have been improved,and the tracking errors in velocity and acceleration have been converged.
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