Abstract:

In order to reduce the error of the Bayesian network algorithm for the assessment of ship situation in the dynamic area of the ocean, an improved algorithm for the assessment of the ship situation is proposed based on the dynamic Bayesian network. The algorithm makes an inference based on the data from multiple sensors and newly acquired situation information. By calculating the mutual information between new situational elements and original situational elements, the dynamic Bayesian network parameters are constructed and updated. Compared with the model of the traditional Bayesian Network, the error rate of the cooperative target of the ship reduces by 7.1% through simulation of about 10,000 ships. By using the improved dynamic Bayesian network algorithm for the assessment of ship situation, under the measured data, the cooperation of situation for the target has increased by 4.2%. The algorithm proposed in this paper not only reflects the environment of ship changes in real time, but also improves the accuracy of the target situation, thus providing a technical support for analysis and decision-making of the situation of ships for Marine Surveillance.

Key words: information fusion, situation assessment, ship target, dynamic Bayesian network, data analysis