Advertisement

Gyroscopy and Navigation

, Volume 9, Issue 4, pp 255–266 | Cite as

Sigma-Point Kalman Filter Algorithm in the Problem of GNSS Signal Parameters Estimation in Non-Coherent Tracking Mode in Spacecraft Autonomous Navigation Equipment

  • V. V. ShavrinEmail author
  • V. I. Tislenko
  • V. Yu. Lebedev
  • V. A. Filimonov
  • A. S. Konakov
Article
  • 8 Downloads

Abstract

The paper presents a multiloop system for noncoherent tracking of the radionavigation parameters of global navigation satellite system (GNSS) signals in autonomous satellite navigation system. Comparative analysis of accuracies of traditional tracking system with discriminators and filter in the tracking loop and the proposed system without discriminators is conducted. RMS errors of estimates, pull-in range and the probability of signal acquisition are studied under various SNR values. Experimental tests of derived noncoherent tracking loop are performed.

Keywords

parameters estimation time delay Kalman filter correlator correlation integral noncoherent tracking loop 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Perov, A.I., and Kharisov, V.N., GLONASS: printsipy postroeniya i funktsionirovaniya (GLONASS: Principles of Construction and Functioning), Moscow: Radiotekhnika, 2010.Google Scholar
  2. 2.
    Kaplan, E.D., and Hegarty, C.J., Understanding GPS. Principles and Applications, Artech House, 2006, 2nd ed.Google Scholar
  3. 3.
    Mikhailov, N.V., Avtonomnaya navigatsiya kosmicheskikh apparatov pri pomoshchi sputnikovykh radionavigatsionnykh sistem (Autonomous Navigation of Spacecraft Using Radionavigation Satellite Systems), St. Petersburg: Politekhnika, 2014.Google Scholar
  4. 4.
    Psiaki, M.L., and Jung, H., Extended Kalman filter methods for tracking weak GPS signals, Proceedings of ION GPS 2002, Portland, USA, 2002, pp. 2539–2553.Google Scholar
  5. 5.
    Ziedan N.I., and Garrison J.L., Bit synchronization and Doppler frequency removal at very low carrier to noise ratio using a combination of the Viterbi algorithm with an extended Kalman filter, Proceedings of ION GPS 2003, Portland, USA, 2003, pp. 616–627.Google Scholar
  6. 6.
    Ziedan, N.I., and Garrison, J.L., Extended Kalman filter-based tracking of weak GPS signals under high dynamic conditions, Proceedings of ION GNSS 2004, Long Beach, USA, 2004, pp. 20–31.Google Scholar
  7. 7.
    Ren, T., Petovello, M.G., and Basnayake, C., Requirements analysis for bit synchronization and decoding in a standalone high-sensitivity GNSS receiver, Proceedings of Ubiquitous Positioning, Indoor Navigation, and Location Based Service (UPINLBS), Helsinki, Finland, 2012, pp. 1–9.Google Scholar
  8. 8.
    Ding, J., Zhang, G., and Zhao, L., Urban and indoor weak signal tracking using an array tracker with MVA and nonlinear filtering, Journal of Applied Mathematics, 2014.CrossRefGoogle Scholar
  9. 9.
    Petovello, M.G., O’Driscoll, C., and Lachapelle, G., Carrier phase tracking of weak signals using different receiver architectures, Proceedings of ION NTM 2008, San Diego, CA, 2008.Google Scholar
  10. 10.
    Perov, A.I., and Korogodin, I.V., Synthesis and analysis of algorithms for estimating the power of the signal and the noise components at the correlator’s output, Radiotekhnika, 2011, no. 7, pp. 76–82.Google Scholar
  11. 11.
    Falletti, E., Pini, M., Lo Presti, L., GNSS solutions: carrier-to-noise algorithms, Inside GNSS, 2010, Jan/Feb, pp. 20–27.Google Scholar
  12. 12.
    Shavrin, V.V., Filimonov, V.A., Lebedev, V.Yu., Tislenko, V.I., Kravets, A.P., and Konakov, A.S., Quasioptimal estimation of GNSS signal parameters in coherent reception mode using sigma-point Kalman filter, Gyroscopy and Navigation, 2017, vol. 8, no. 1, pp. 24–30.CrossRefGoogle Scholar
  13. 13.
    Sarkka, S., Bayesian Filtering and Smoothing, Cambridge University Press, 2013.CrossRefzbMATHGoogle Scholar
  14. 14.
    Tikhonov, V.I., and Kharisov, V.N., Statisticheskii analiz i sintez radiotekhnicheskikh ustroistv i sistem (Statistical Analysis and Synthesis of Radiotechnical Devices and Systems), Moscow: Radio i svyaz', 1991.Google Scholar
  15. 15.
    Simandl, M., Lecture Notes on State Estimation of Nonlinear Non-Gaussian Stochastic Systems, Pilsen: University of West Bohemia, 2006.Google Scholar
  16. 16.
    Im, S., Song, J., Jee, G., and Park, C., Comparison of GPS tracking loop performance in high dynamic condition with nonlinear filtering techniques, ION GNSS 21st International Technical Meeting of Satellite Division, 2008. pp 2351–2360.Google Scholar
  17. 17.
    Korogodin, I.V., Potential performance of frequency estimation for non-coherent receiver, Radiotekhnika, 2013, no. 7, pp. 109–115.Google Scholar
  18. 18.
    Boldenkov, E.N., Complex delay and frequency of GNSS signal tracking algorithm based on optimal trajectory filtering techniques, Radiotekhnika, 2013, no. 10, pp. 103–106.Google Scholar
  19. 19.
    Gonorovskii, I.S., Radiotekhnicheskie tsepi i signaly (Radiotechnical Circuits and Signals): uchebnik dlya vuzov (Textbook for Higher Educational Establishments), 4th ed., Moscow: Radio i svyaz', 1986.Google Scholar
  20. 20.
    Doucet, A., and Johansen A., A tutorial on particle filtering and smoothing: fifteen years later. In: Crisan, D., Rozovsky, B. (eds.) Oxford Handbook of Nonlinear Filtering, OUP, Oxford, 2009.zbMATHGoogle Scholar
  21. 21.
    Merwe, R., Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models, PhD Thesis, 2004.Google Scholar
  22. 22.
    Candy, J.V., Bayesian Signal Processing. Classical, Modern, and Particle Filtering Methods, John Wiley & Sons, Inc., 2009.Google Scholar
  23. 23.
    Julier, S.J., and Uhlman, J.K., A new extension of the Kalman filter to nonlinear systems, Proc. of AeroSence, the 11th Intern. Symp. On Aerospace/Defence Sensing, Simulation and Controls, Orlando FL, USA. 1997.Google Scholar
  24. 24.
    Borre, K., Akos, D.M., Bertelsen, N., Rinder, P., and Jensen, S.H., A Software-Defined GPS and Galileo Receiver. A Single-Frequency Approach, Boston: Birkhauser, 2007.zbMATHGoogle Scholar
  25. 25.
    https://doi.org/www.datatec.de/shop/artikelpdf/n5182b_d.pdf, Keysight Technologies, MXG X-Series Signal Generators, N5181B Analog & N5182B Vector, Datasheet, accessed 23.07.2018.
  26. 26.
    Juang J.-C., and Chen Y.-H., Phase/frequency tracking in a GNSS software receiver, IEEE Journal of Selected Topics in Signal Processing, 2009, no. 3 (4), pp. 651–660.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • V. V. Shavrin
    • 1
    Email author
  • V. I. Tislenko
    • 1
  • V. Yu. Lebedev
    • 1
  • V. A. Filimonov
    • 1
  • A. S. Konakov
    • 1
  1. 1.Tomsk University of Control Systems and RadioelectronicsRadiotechnical Systems DepartmentTomskRussia

Personalised recommendations