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Models of Onboard Reconstruction of Sea Current Parameters as a Navigation Factor According to GLONASS Data

https://doi.org/10.17587/mau.19.601-607

Abstract

A methodology is proposed for investigating surface sea currents that considered as natural phenomena. Monitoring of sea currents is relevant in the context of ensuring the safety and purposefulness of a variety of human activities at the sea. The peculiarity of this methodology, which distinguishes it from others, is that it identifies the current with the portable movement of a controlled marine object. It considered as a navigational factor that changes in time and geographical space and requires an on-board operational assessment of the current state. Mathematical models of inverse trajectory problems of the "state — measurement" form are presented, the aim and main component of the solutions is the velocity vector estimation of the sea current, following the reconstruction of the object absolute velocity (relatively to solid Earth) according to its GLONASS positioning data. These models are associated with the model of the estimating the derivatives problem of a continuous time function from its temporally measurable values having the Jordan form of a matrix with a nilpotency index that coincides with the dimension of the system of linear differential equations of state, which causes the discretization of the problem in time without methodological errors and the implementation of computational algorithms for dynamic circulation. The results of computational experiments are presented.

About the Authors

A. S. Devyatisilny
Institute of Automation and Control Processes, Far Eastern Branch of RAS
Russian Federation

Ph. D., Professor, Head of the Navigation and Control Department



A. V. Shurygin
Institute of Automation and Control Processes, Far Eastern Branch of RAS
Russian Federation


References

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Review

For citations:


Devyatisilny A.S., Shurygin A.V. Models of Onboard Reconstruction of Sea Current Parameters as a Navigation Factor According to GLONASS Data. Mekhatronika, Avtomatizatsiya, Upravlenie. 2018;19(9):601-607. (In Russ.) https://doi.org/10.17587/mau.19.601-607

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ISSN 1684-6427 (Print)
ISSN 2619-1253 (Online)