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A Method of Combining Data from Electronic Maps and Satellite Measurements for High-Precision Positioning of Moving Objects

https://doi.org/10.17587/mau.24.551-559

Abstract

A new approach to the processing of satellite navigation measurements for high-precision positioning of moving objects moving along a priori (program) trajectories is considered. Existing methods of processing satellite information using the least squares method or its various modifications provide the required positioning accuracy mainly only for stationary objects. At the same time, to assess the state of highly dynamic objects, taking into account the noise of satellite measure- ments, it is very effective to use modern methods of stochastic filtering theory, taking into account both the unevenness of the movement of a transport object and errors in the processing of measurements. The considered approach is based on the use of these methods of nonlinear stochastic filtering. It is proposed to increase the accuracy of positioning a moving object using electronic maps. The use of a digital path model makes it possible to approximate with a given accuracy the a priori (program) trajectory of a moving object with a set of trajectory intervals — orthodromies. These intervals allow you to establish an analytical dependence on the navigation parameters, which ensures high positioning accuracy and a significant reduction in computational costs. The integration of information from electronic maps and stochastic filtering algorithms for dynamic processing of satellite measurements made it possible to significantly reduce computational costs when estimating the current coordinates of a moving object and at the same time significantly improve positioning accuracy compared to traditional methods of processing satellite messages.

About the Authors

S. V. Sokolov
Moscow Technical University of Communications and Informatics (MTUCI), North Caucasus Branch
Russian Federation

Rostov-on-Don, 344002



V. A. Pogorelov
Don State Technical University
Russian Federation

Rostov-na-Donu, 344003



A. L. Okhotnikov
Research and Design Institute for Information Technology, Signalling and Telecommunications on Railway Transport (JSC NIIAS)
Russian Federation

Deputy Head of the Information Technology Department — Head of the Strategic Development Department

Moscow, 107078



M. V. Kurinenko
Moscow Technical University of Communications and Informatics (MTUCI), North Caucasus Branch
Russian Federation

Rostov-on-Don, 344002



References

1. Bhatti J., Humphreys T. Hostile control of ships via false GPS signals: Demonstration and detection, NAVIGATION: Journal of The Institute of Navigation, Spring 2017, vol. 64, no. 1, DOI 10.1002/navi.183.

2. Mikrin E., Mikhailov M. Navigation of spacecraft by measurements from global satellite navigation systems, Moscow, Publishing house of Bauman Moscow State Technical University, 2017, 344 p. (in Russian).

3. Rosenberg I. N., Sokolov S. V., Umansky V. I., Pogorelov V. A. Theoretical bases of close integration of inertial-satellite navigation systems, Moscow, FIZMATLIT, 2018, 312 p. (in Russian).

4. Sokolov S. V., Pogorelov V. A. Stochastic estimation, control and identification in high-precision navigation systems, Moscow, LLC Publishing company "Physico-mathematical Literature", 2016, 264 p. (in Russian)

5. Emeliantsev G. I., Stepanov A. P. Integrated inertialsatellite systems of orientation and navigation, Saint Petersburg, Concern "Central Research Institute "Electropribor", 2016, 394 p. (in Russian).

6. Perov A. I., Kharisov V. N. ed. GLONASS. Principles of construction and functioning, Moscow, Radiotekhnika, 2010, 800 p. (in Russian).

7. Kinkulkin I. E. Global navigation satellite systems: algorithms for the functioning of consumer equipment, Moscow, Radiotekhnika, 2018, 325 p. (in Russian).

8. Jin T., Hu B., Sun Y. et al. Optimal Solution to MultiFrequency BDS Code-Multipath Combination Measurement, The Journal of Navigation, 2019, vol. 72, no. 5, pp. 1297—1314, DOI 10.1017/S0373463319000158.

9. Kosarev N. S., Padve V. A., Sergeev S. A., Dudarev V. I. Using the synthesized version of the algorithm of the parametric version of the MNC-optimization of GNSS measurement results for their comparative analysis, Bulletin of the Siberian State University of Geosystems and Technologies, 2018, vol. 23, no. 3, pp. 30—45 (in Russian).

10. Al Bitar N., Gavrilov A. A novel approach for aiding unscented Kalman filter for bridging GNSS outages in integrated navigation systems, Navigation, Journal of the Institute of Navigation, 2021, vol. 68, no. 3, pp. 521—539, DOI 10.1002/navi.435.

11. Sage A. P., Melsa J. L., Steinway W. J. Estimation Theory with Applications to Communication and Control, IEEE Transactions on Systems, Man, and Cybernetics, Oct. 1971, vol. SMC-1, no. 4, pp. 405—405, DOI: 10.1109/TSMC.1971.4308330.

12. Sinitsyn I. N. Kalman and Pugachev, Moscow, Logos, 2007, 772 p. (in Russian).

13. Tikhonov V. I., Kharisov V. N. Statistical analysis and synthesis of radio engineering devices and systems: Textbook for universities, Moscow, Radio i svyaz, 2004, 608 p. (in Russian).

14. Asgari M., Khaloozadeh H. Robust extended Kalman filtering for nonlinear systems with unknown input: a UBB model approach, IET Radar, Sonar and Navigation, 2020, Vol. 14, no. 11, pp. 1837—1844, DOI 10.1049/iet-rsn.2020.0258.

15. Herrera E. P., Kaufmann H. Adaptive Methods of Kalman Filtering for Personal Positioning Systems, Proceedings of the 23rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2010), Portland, OR, September 2010, pp. 584—589.

16. Hu C., Chen W., Chen Y., Liu D. Adaptive Kalman Filtering for Vehicle Navigation, Journal of Global Positioning Systems, 2003, vol. 2, no. 1, pp. 42—47, DOI:10.5081/jgps.2.1.42.

17. Kerns A. J., Shepard D. P., Bhatti J. A., Humphreys T. E. Unmanned aircraft capture and control via GPS spoofing, Journal of Field Robotics, 2014, vol. 31, no. 4, pp. 617—636, DOI 10.1002/ rob.21513.

18. Kucherenko P. A., Sokolov S. V. Analytical Solution of the Navigation Problem on the Orthodromic Trajectory in the Greenwich Coordinate System, Mechanics of Solids, 2018, vol. 53, Suppl. 2, pp. 133—134, DOI 10.3103/S0025654418050114.

19. Lukasevich V. I., Pogorelov V. A., Sokolov S. V. Nonlinear filtering of vehicle motion parameters in an integrated navigation system using electronic map data, Russian Aeronautics, 2015, vol. 58, no. 3, рр. 338—344, DOI 10.3103/S1068799815030150.

20. Kos S., Zec D., Vrani@ D. Differential Equation of a Loxodrome on a Sphere, Journal of Navigation, 1999, vol. 52, no. 3, рр. 418—420, DOI 10.1017/S0373463399008395.

21. Certificate of state registration of the computer program No. 2018666659 Russian Federation. Software package for determining the parameters of orthodromic trajectories: No. 2018663785: application 03.12.2018: publ. 19.12.2018 / E. V. Zhilina, S. V. Sokolov, E. N. Tishchenko; applicant Federal State Budgetary Educational Institution of Higher Education "Rostov State University of Economics (RINH)" (in Russian).


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For citations:


Sokolov S.V., Pogorelov V.A., Okhotnikov A.L., Kurinenko M.V. A Method of Combining Data from Electronic Maps and Satellite Measurements for High-Precision Positioning of Moving Objects. Mekhatronika, Avtomatizatsiya, Upravlenie. 2023;24(10):551-559. (In Russ.) https://doi.org/10.17587/mau.24.551-559

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