Abstract
In Vessel Traffic Services (VTS), multi-radar network cannot only expand service area of VTS, but also improves the reliability and quality of target tracking through data fusion from multiple radars. However, without registering system error of radar before beginning multi-radar data fusion in VTS, the quality of target tracking would not be credible. Currently, Extended Kalman Filter (EKF) is often used to solve error registration of radar system by online bias estimation, but because linearization error will reduce the accuracy of the model of EKF, its estimation accuracy will become worse with time. Unscented Kalman filter (UKF) is a filtering algorithm based on unscented transform, which directly uses the nonlinear model to avoid the linearization error and derivative calculation of Jacobian matrix. Compared with the EKF, UKF is much easier to be implemented and its estimation accuracy and convergence speed have been improved. Therefore, UKF is proposed to finish error registration of radar network system in VTS and the simulation results have verified the feasibility and effectiveness.
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