With the rapid development of marine fishery informatization, how to achieve accurate monitoring through fishing vessel data is an important research direction to improve the intelligent level of marine traffic supervision. In this study, VSAT and BDS technologies are used to build an intelligent monitoring system for fishing vessels to effectively supervise them. In order to realize accurate fishing vessel position prediction, the improved joint probabilistic data association algorithm is used to realize the fusion of information VSAT and BDS, and then the LSTM-based fishing vessel position prediction method is designed. Comparison experiments show that the average accuracy of this paper’s algorithm for fishing vessel position fishing vessels are above 80%, which is improved by 8.6%~14.8% and 5.3%~13.4% in the training set and test set, respectively, and the standard deviation of prediction accuracy is 3.07, which is significantly smaller than the comparison method. The JPDA-LSTM algorithm has a superior prediction performance compared with other comparison algorithms, and can meet the fishing vessel needs of intelligent monitoring.
