Непрерывные фильтры частиц и их реализация в реальном масштабе времени

Authors

  • Константин Александрович Рыбаков Moscow Aviation Institute (National Research University)
  • Артем Анатольевич Ющенко Moscow Aviation Institute (National Research University)

DOI:

https://doi.org/10.17308/sait.2018.3/1231

Keywords:

optimal estimation, optimal filtering problem, parallel programming, stochastic system, stochastic differential equations, particle filter

Abstract

The main goal is the development and testing of the optimal estimation software for continuoustime stochastic system trajectories. This estimation is based on the results of measurements using continuous-time particle filters. The software is developed with OpenMP, Microsoft Visual Studio and Intel Parallel Studio (C/C++ programming language). The developed software implements two variants of particle filters for continuous-time stochastic systems. The tracking for coordinates and speeds of an aircraft that executes a maneuver in the horizontal plane is considered as an example.

Author Biographies

  • Константин Александрович Рыбаков, Moscow Aviation Institute (National Research University)

    candidate of physico-mathematical sciences, associate professor, Mathematical cybernetics department, Moscow aviation institute (national research university)

  • Артем Анатольевич Ющенко, Moscow Aviation Institute (National Research University)

    магистрант кафедры «Математическая кибернетика», Московский авиационный институт (национальный исследовательский университет)

References

Downloads

Published

2018-06-06

Issue

No. 3 (2018): July - September

Section

Mathematical Methods of System Analysis and Management

License

Условия передачи авторских прав in English

How to Cite

Непрерывные фильтры частиц и их реализация в реальном масштабе времени. (2018). Proceedings of Voronezh State University. Series: Systems Analysis and Information Technologies, 3, 56-64. https://doi.org/10.17308/sait.2018.3/1231