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Analytical Decision of Adaptive Estimation Task for Measurement Noise Covariance Matrix Based on Irregular Certain Observations

  • Sergey V. Sokolov
  • Andrey V. SukhanovEmail author
  • Elena G. Chub
  • Alexander A. Manin
Conference paper
  • 13 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1156)

Abstract

The problem of adaptive estimation for measurement noise covariance matrix in Kalman filter is analytically solved based on accurate observations obtained irregularly. The results of numerical modeling are provided. These results illustrate the key advantages of state vector stochastic estimation algorithm based on proposed approach in comparison to conventional one.

Keywords

Irregular accurate observations Measurement noise covariance matrix Kalman filter Adaptive estimation 

Notes

Acknowledgement

This work was supported by RFBR (Grants No. 17-20-01040 ofi_m_RZD, No. 18-07-00126).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sergey V. Sokolov
    • 1
  • Andrey V. Sukhanov
    • 1
    • 2
    Email author
  • Elena G. Chub
    • 1
  • Alexander A. Manin
    • 3
  1. 1.Rostov State Transport UniversityRostov-on-DonRussia
  2. 2.JSC NIIAS, Rostov BranchRostov-on-DonRussia
  3. 3.Moscow Technical University of Communications and InformaticsRostov-on-DonRussia

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