COMPARATIVE ANALYSIS OF INFORMATION INTEGRATION SCHEMES  STERILE INERTIAL NAVIGATION SYSTEMS FOR UNMANNED VEHICLES  AIRCRAFT

P. Ermakov; A. Gogolev

doi:10.31618/ESSA.2782-1994.2021.3.76.213

Автор(и)

P. Ermakov Государственный научно-исследовательский институт авиационных систем, ГосНИИАС
A. Gogolev Ермаков П.Г.*, Гоголев А.А.** Государственный научно-исследовательский институт авиационных систем, ГосНИИАС

DOI:

https://doi.org/10.31618/ESSA.2782-1994.2021.3.76.213

Ключові слова:

имитационное моделирование; беспилотный летательный аппарат; навигационная система; раздельная схема комплексирования; слабосвязанная схема комплексирования; фильтр Калмана

Анотація

A serious problem with modern unmanned aerial vehicles weighing less than 500 kg is their low reliability due to the significant mass limitations of the information management complex, which in turn leads to the use of microelectromechanical (MEMA) Sensors with significant care and drift [1]. This article provides a comparative analysis of the separate and loosely linked integration schemes based on the simulation of the VN-100T inertial-measurement module and navigation algorithms with the aim of increasing the accuracy and reliability of the informationThe manager of the unmanned aerial vehicle (UAV) complex.

Посилання

Zakriya Mohammed, Ibrahim (Abe) M. Elfadel, Mahmoud Rasras. Monolithic Multi Degree of Freedom (MDoF) Capacitive MEMS Accelerometers // Micromachines, 16 November 2018, vol. 9, no. 11. DOI: 0.3390/mi9110602

Gogolev A.A., Gorobinskij M.A. Opredelenie sobstvennogo polozhenija mikrobespilotnogo letatel'nogo apparata v uslovijah zamknutogo prostranstva // Trudy MAI. 2018. № 101. URL: https://mai.ru/publications/index.php?ID=97029

Krasil'shhikov M.N., Serebrjakov G.G. Sovremennye informacionnye tehnologii v zadachah navigacii i navedenija bespilotnyh manevrennyh letatel'nyh apparatov. – M.: FIZMATLIT, 2009. – 556 s.

Savel'ev V.M., Antonov D.A. Vystavka besplatformennoj inercial'noj navigacionnoj sistemy bespilotnogo letatel'nogo apparata na podvizhnom osnovanii // Trudy MAI. 2011. № 45. URL: http://trudymai.ru/published.php?ID=25497&PAGEN _2=2

Kolosovskaja T.P. Suboptimal'nyj algoritm ocenivanija i parametricheskoj identifikacii dlja navigacionnyh sistem letatel'nyh apparatov i drugih podvizhnyh ob#ektov na osnove informacii magnitnogo polja Zemli // Trudy MAI. 2016. № 88. URL: http://trudymai.ru/published.php?ID=70666

Alex G Quinchia, Gianluca Falco, Emanuela Falletti, Fabio Dovis. A Comparison between different error modeling of MEMS applied to GPS / INS integrated systems // Sensors (Basel), 24 July 2013, vol. 13, no. 3, pp. 9549 – 9588. DOI:10.3390/s130809549

Calogero Cristodaro, Laura Ruotsalainen, Fabio Dovis. Benefits and Limitations of the Record and Replay Approach for GNSS Receiver Performance Assessment in Harsh Scenarios // Sensors, 7 July 2018, vol. 18, no. 7. DOI: 10.3390/s18072189

Liu Hong Dan, Shu Xiong Ying, Li Xi Sheng. Application Of Strongly Tracking Kalman Filter In MEMS Gyroscope Bias Compensation // 6th International Conference on Advanced Materials and Computer Science, ISAMCS 2017. DOI:

23977/icamcs.2017.1004

Accelerometer Errors, 9 July 2015. URL: http://kionixfs.kionix.com/en/document/AN012%20Accelerometer%20Errors.pdf

Vlada Sokolović, Goran Dikić, Rade Stančić. Adaptive Error Damping in the Vertical Channel of the Ins/Gps/Baro – Altimeter Integrated Navigation System // Scientific Technical Review, 2014, vol. 64, no. 2, pp. 14 – 20.

Alberto Manero Contreras, Chingiz Hajiyev. Fault Tolerant Integrated Barometric-Inertial GPS Altimeter // 7th European conferences for aeronautics and aerospace science (EUCASS), 2017. DOI: 10.13009 / EUCASS2017 – 62

Tang. Pham Van, Thang Nguyen Van, Duc Anh Nguyen, Trinh Chu Duc. 15 – State Extended Kalman Filter Design for INS / GPS Navigation System // Journal of Automation and Control Engineering, January 2015, vol. 3, no. 2, pp. 109 -114. DOI: 10.12720/joace.3.2.109-114

Beard & McLain. Small Unmanned Aircraft, Princeton University Press, 2012. URL: https://uavbook.byu.edu/doku.php

Yan Chen, Dan Li, Yanhai Li, Xiaoyuan Ma. Use Moving Average Filter to Reduce Noises in Wearable PPG During Continuous Monitoring // EAI International Conference on Wearables in Healthcare, Budapest, Hungary, vol. eHealth 2016, LNICST 181, pp. 193 – 203. DOI: 10.1007/978-3-319-49655-9_26

Mushfiqul Alam, Jan Rohac. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth // Sensors, February 2015, vol. 15, no. 2, pp. 3282 - 3298. DOI: 10.3390/s150203282

Paola Pierleoni, Alberto Belli, Lorenzo Maurizi, Lorenzo Palma. A Wearable Fall Detector for Elderly People Based on AHRS and Barometric Sensor// Sensors, September 2016, vol. 16, no. 17, pp. 1 - 1. DOI: 10.1109/JSEN.2016.2585667

Wenjiao Xiao, Zgu, Yu. An Unconventional Multiple Low-Cost IMU and GPS-Integrated Kinematic Positioning and Navigation Method Based on Singer Model // Sensors, October 2019, vol. 19, no. 19. DOI: 10.3390/s19194274

Veremeenko K.K., Galaj I.A. Razrabotka algoritma kalibrovki inercial'noj navigacionnoj sistemy na dvuhosnom ispytatel'nom stende // Trudy MAI. 2013. № 63. URL: http://trudymai.ru/published.php?ID=36139

Kuznecov I.M., Pron'kin A.N., Veremeenko K.K. Navigacionnyj kompleks ajeroportovogo transportnogo sredstva // Trudy MAI. 2011. № 47. URL: http://trudymai.ru/published.php?ID=26966

Vishal Awasthi, Krishna Raj. A Comparison of Kalman Filter and Extended Kalman Filter in State Estimation // International Journal of Electronics Engineering, 2011, vol. 3, no. 1, pp. 67 – 71.

Logah Perumal. Representing Rotation in Simulink using Quaternion // Applied Mathematics & Information Science, 1 April 2014, vol. 8, no. 1L, pp. 267 – 272. DOI: 10.12785/amis/081L34

VectorNav Embedded Navigation Solutions. VN – 100 User Manual. URL: https://www.eol.ucar.edu/system/files/VN100manual.pdf