Relatively-Integrated Ship Navigation by H¥ Fusion Filters

Yanping Yang and Ruiguang Li
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Yanping Yang: Yellow River Conservancy Technical Institute, China
Ruiguang Li: Henan University, China

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2021, vol. 15, issue 4, 1-12

Abstract: For the system with unknown statistical property noises, the property that the energies of the system noise and the observation noise are limited is utilized in this paper. On this basis, two novel fusion algorithms are proposed for ship integrated navigation with the relative navigation information, broadcasted by the Automatic Identification Systems (AISs) in the adjacent ships. Firstly, an H∞ fusion filtering algorithm is given to deal with the navigation observation messages, under the centralized fusion framework. The integrated navigation method based on this algorithm cannot deal with the asynchronous navigation messages in real time. Therefore, a sequential H∞ fusion filtering algorithm is also given to sequentially deal with the asynchronous navigation messages, secondly. Finally, a computer simulation is employed to illustrate the validity and feasibility of the sequential method.

Date: 2021
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