student from 01.01.2023 until now
student from 01.01.2023 until now
Russian Federation
The study addresses the problem of improving the accuracy of an autonomous strapdown inertial navigation system (INS) operating without any external corrections. An adaptive algorithm for compensating the accumulation of errors arising during long-term operation of MEMS accelerometers and gyroscopes is presented, including random noise, bias instability, bias random walk, and slow sensitivity drifts. The algorithm relies on dynamic adjustment of the error-model covariances based on the innovation statistics of the Kalman filter, enabling the process parameters to adapt to the current uncertainty level and characteristics of the measurement noise. Numerical simulation of a three-axis INS with realistic sensor parameters is performed, and a comparative analysis of baseline and adaptive filtering schemes is provided. Stability and adaptation-quality metrics are evaluated, including NIS values, normalized-innovation variance, and the evolution of extended covariance matrices. The results indicate a significant reduction of accumulated errors during extended autonomous operation and confirm the applicability of the method for navigation modules of small unmanned aerial vehicles. Additionally, it is shown that adaptive drift compensation enables the use of lower-cost MEMS sensors without a major loss in accuracy, reducing the overall price of the navigation module, lowering the dependency on external correction infrastructure, and increasing the economic efficiency of projects involving large-scale deployment of autonomous unmanned systems
strapdown inertial navigation system, adaptive drift compensation, Kalman filter, autonomous navigation, MEMS sensors, navigation module cost reduction, reduced reliance on external correction, economic efficiency
1. Selivanova L. M., Shevcova E. V. Inercial'nye navigacionnye sistemy. Ch. 1: Odnokanal'nye inercial'nye navigacionnye sistemy: ucheb. posobie. — M.: Izd-vo MGTU im. N. E. Baumana, 2012. — 46 s. — URL: https://library.bmstu.ru/DigitalResources/Download/41148 (data obrascheniya: 10.11.2025).
2. Matveev V. V. Inercial'nye navigacionnye sistemy: ucheb. posobie. — Tula: Izd-vo TulGU, 2012. — 198 s. — URL: https://rusneb.ru/catalog/000200_000018_RU_NLR_bibl_2038305/ (data obrascheniya: 10.11.2025).
3. Emel'yancev G. I., Stepanov A. P., Medvedkov A. A. Integrirovannye inercial'no-sputnikovye sistemy orientacii i navigacii: ucheb. posobie. — SPb.: Universitet ITMO, 2019. — 146 s. — URL: https://djvu.online/file/YBDwwLfLUQQVX (data obrascheniya: 10.11.2025).
4. Mikrin E. A., Mihaylov M. V. Orientaciya, vyvedenie, sblizhenie i spusk kosmicheskih apparatov po izmereniyam ot global'nyh sputnikovyh navigacionnyh sistem: ucheb. posobie. — M.: Izd-vo MGTU im. N. E. Baumana, 2017. — 357 s. — ISBN 978-5-7038-4778-7. — URL: https://library.bmstu.ru/Catalog/Details/492278.
5. Shahtarin B. I. Fil'try Vinera i Kalmana: ucheb. posobie. — M.: Goryachaya liniya — Telekom, 2016. — 396 s.
6. Stepanov O. A. Fil'tr Kalmana: istoriya i sovremennost' // Giroskopiya i navigaciya. — 2010. — № 2 (69). — S. 107–121. — URL: http://bias.ipiran.ru/database/article/view/id/7705.html (data obrascheniya: 03.11.2025).
7. Sage A. P., Husa G. W. Adaptive filtering with unknown prior statistics // Proceedings of the Joint Automatic Control Conference. — Boulder, CO, 1969. — P. 760–769.
8. Shvedenko V. N., Viktorov A. S. Sovershenstvovanie algoritma vizual'noy odometrii dlya resheniya zadachi odnovremennoy navigacii BPLA i postroeniya karty zemnoy poverhnosti // Nauchno-tehnicheskiy vestnik informacionnyh tehnologiy, mehaniki i optiki. — 2017. — T. 17, № 3. — S. 475–482. — DOI:https://doi.org/10.17586/2226-1494-2017-17-3-475-482. — URL: https://ntv.ifmo.ru/file/article/16763.pdf (data obrascheniya: 03.11.2025).
9. Kovalev M. A., Hablo I. I., Zolotarev A. L., Velizhanin S. P., Elufimov D. S. Radiotehnicheskie navigacionnye sredstva samoletovozhdeniya i posadki. Ch. 1: Ucheb. posobie. — Samara: SGAU, 2011. — 76 s. — URL: https://repo.ssau.ru/handle/Uchebnye-posobiya/Radiotehnicheskie-navigacionnye-sredstva-samoletovozhdeniya-i-posadki-ucheb-posobie-Ch-1-Radiotehnicheskie-navigacionnye-sredstva-samoletovozhdeniya-i-posadki-ucheb-posobie-55178 (data obrascheniya: 03.11.2025).
10. Malikov R. F. Metod Monte-Karlo: uchebnik dlya vuzov. — 2-e izd. — M.: Yurayt, 2025. — 96 s. — (Vysshee obrazovanie). — ISBN 978-5-534-19869-0. — URL: https://urait.ru/book/metod-monte-karlo-581016 (data obrascheniya: 10.11.2025).
11. Klimenko M. Podavlenie uzkopolosnyh pomeh v signalah GNSS s pomosch'yu KIH-fil'trov // Elektronika: nauka, tehnologiya, biznes. — 2016. — № 2. — S. 112–119. — URL: https://www.electronics.ru/journal/article/5142 (data obrascheniya: 03.11.2025).
12. Kascheev A. A., Koshelev V. I. Ocenka effektivnosti podavleniya signalov sputnikovyh radionavigacionnyh sistem prednamerennymi pomehami // Zhurnal radioelektroniki. — 2012. — № 7. — S. 1–12.
