Abstract: In order to integrate the vessels’ tracks from different monitoring sources and form a unified maritime posture, a track correlation identification method based on track prediction and fuzzy membership evaluation is proposed. A polynomial fitting method is used to speculate the past and future tracks. Position, course, and speed are selected as the fuzzy factors. The membership degree of each fuzzy factor between the predicted track is calculated by ridge fuzzy membership function and weighted to obtain the membership of a single moment. A weighting function is constructed to calculate the comprehensive membership degree and finally the threshold is set to determine whether the two tracks are correlated. In simulation experiments, the precision and the recall rate of the proposed method is higher than 90% and 80% respectively, which outperforms the traditional method. In order to further investigate the applicability of the proposed method, the radar monitoring data of vessel tracks under different scenarios are simulated, including stable scenarios, speed change and course change scenarios during the interruption interval. Simulation results show that the proposed method provides an effective way to solve the problem of correlation identification of interrupted tracks in the cross environment of non-cooperative vessels.

Key words: interrupt track, track correlation, track prediction, ridge-type fuzzy membership degree