RUDN Journal of Engineering ResearchRUDN Journal of Engineering ResearchВестник Российского университета дружбы народов. Серия: Инженерные исследования2312-81432312-8151Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)3854810.22363/2312-8143-2024-25-1-57-74DZDZTSArticlesСтатьиReview ArticleOptimizing MEMS-based navigation sensors for aerospace vehiclesОптимизация навигационных сенсоров на основе МЭМС для аэрокосмических транспортных средствhttps://orcid.org/0009-0006-0673-18931755-9674AlizadehAliАлизадехАли

M.S Student of Control in Technical Systems-Space Engineering of the Department of Mechanics and Control Processes, Academy of Engineering, RUDN University; M.S Student of Space Engineering, Faculty of Aerospace Engineering, K.N. Toosi University of Technology

магистрант департамента механики и процессов управления, инженерная академия, Российский университет дружбы народов, Москва, Россия; студент магистратуры космической техники, факультет аэрокосмической техники

ali.rim.alizadeh@gmail.comhttps://orcid.org/0000-0002-3880-66623969-6707SaltykovaOlga A.СалтыковаОльга Александровна

Ph.D. of Physico-mathematical Sciences, Associate Professor of the Department of Mechanics and Control Processes, Academy of Engineering

кандидат физико-математических наук, доцент департамента механики и процессов управления, инженерная академия

saltykova-oa@rudn.ruNovinzadehAlireza B.НовинзадехАлиреза Б.Ph.D. of Space Engineering, Associate Professor and Head of the Department of Space Engineering, Faculty of Aerospace Engineeringдоктор наук в области космической инженерии, доцент и заведующий кафедрой космической инженерии, факультет аэрокосмической инженерииnovinzadeh@kntu.ac.irRUDN UniversityРоссийский университет дружбы народовK.N. Toosi University of TechnologyТехнологический университет имени К.Н. Туси15032024251VOL 25, NO1 (2024)ТОМ 25, №1 (2024)577402042024Copyright ©; 2024, Alizadeh A., Saltykova O.A., Novinzadeh A.B.Copyright ©; 2024, Ализадех А., Салтыкова О.А., Новинзадех А.Б.2024Alizadeh A., Saltykova O.A., Novinzadeh A.B.Ализадех А., Салтыкова О.А., Новинзадех А.Б.https://creativecommons.org/licenses/by-nc/4.0/legalcodehttps://journals.rudn.ru/engineering-researches/article/view/38548

This comprehensive study delves deeply into the intricate domain of optimizing Micro-electromechanical Systems (MEMS)-based navigation sensors for aerospace vehicles. It entails a meticulous examination of MEMS sensors, focusing on their role in guidance, navigation, and control, with particular emphasis on MEMS inertial sensors and crucial performance metrics. The study investigates a spectrum of techniques for sensor optimization, including strategies for enhancing fabrication and production through smart structures and mathematical modeling. Additionally, it explores methodologies and mechanisms for improving navigation sensor fabrication, along with the incorporation of optimizer techniques to manage computational complexities effectively. The key findings underscore the challenges tied to material selection and structural intricacies in optimizing these sensors for aerospace applications. Integration of sensors into integrated circuits, development of advanced mathematical models, and harmonization with artificial intelligence algorithms are vital for boosting sensor performance, while calibration and error mitigation during user deployment are essential. Furthermore, the study underscores the imperative for addressing limitations in sensor accuracy and precision through refined calibration mechanisms and error correction processes. The trajectory for future research involves advancing material selection, mathematical models, and innovative calibration techniques to comprehensively enhance sensor performance and reliability in aerospace applications.

Проведен анализ исследований, посвященных оптимизации навигационных датчиков, выполненных на основе микроэлектро-механических систем (МЭМС) для аэрокосмических транспортных средств. Рассмотрены МЭМС-датчики, их задачи в управлении, навигации и контроле, особенности инерционных МЭМС-датчиков и важные показатели их производительности. Исследован широкий спектр методов оптимизации датчиков, включая стратегии улучшения производства, изготовления через смарт-структуры и математическое моделирование. Исследованы методология и механизмы улучшения производства навигационных датчиков, а также внедрение методов оптимизации для эффективного управления вычислительными сложностями алгоритмов. Основные результаты подчеркивают вызовы, связанные с выбором материалов и структурными сложностями при оптимизации МЭМС-датчиков для аэрокосмических задач. Интеграция датчиков в интегральные схемы, разработка продвинутых математических моделей и согласование с алгоритмами искусственного интеллекта необходимы для повышения производительности датчиков. Калибровка и устранение ошибок при развертывании датчиков пользователем являются обязательными этапами их внедрения. В работе подчеркивается необходимость нахождения способов для снятия ограничений по точности и прецизионности датчиков путем совершенствования механизмов калибровки и процессов коррекции ошибок. Сделан вывод о том, что направления дальнейших исследований лежат в области разработки новых материалов, построения более точных математических моделей и применения инновационных методов калибровки для всестороннего улучшения производительности и надежности МЭМС-датчиков в аэрокосмических приложениях.

performance metricscalibrationinertial sensorsArtificial Intelligencemathematical modelingsmart structuresпоказатели производительностикалибровкаинерционные датчикиискусственный интеллектматематическое моделированиеинтеллектуальные конструкцииZukersteinova A. Skill Needs in Emerging Technologies: Nanotechnology. Cedefop; 2007.Salomon P. MEMS - Recent Developments, Future Directions.Litman K. Static and dynamic assessment of the accuracy and precision of FOUR SHIMMER 2r microelectronic measuring systems (MEMS). 2015.Osiander R, Champion J, Darrin MAG. MEMS and Microstructures in Aerospace Applications. Taylor & Francis; 2006.Gaura E, Newman R, Kraft M, Flewitt A. Smart MEMS and sensor systems. Imperial College Press (ICP); 2006.Janson SW. Aerospace applications of MEMS. In: MEMS/MOEMS Components and Their Applications II. Vol. 5717. SPIE; 2005:1. https://doi.org/10.1117/12.601836Ko WH. Trends and frontiers of MEMS. Sens Actuators A Phys. 2007;136(1):62-67. https://doi.org/10.1016/j.sna.2007.02.001Liddle JD, Holt AP, Jason SJ, O’Donnell KA, Stevens EJ. Space science with CubeSats and nanosatellites. Nat Astron. 2020;4(11):1026-1030. https://doi.org/10.1038/S41550-020-01247-2Winkler S, Buschmann M, Kruger L, Schulz HW, Vorsmann P. Multiple Sensor Fusion for Autonomous Mini and Micro Aerial Vehicle Navigation. 2007.Wilson WC, Atkinson GM, Barclay RO. NASA NDE Applications for Mobile MEMS Devices and Sensors.Barhoum A, Altintas Z. Advanced Sensor Technology_ Biomedical, Environmental, and Construction Applications-Elsevier (2022). Published online 2022.PHM Society, American Industrial Arts Association, Institute of Electrical and Electronics Engineers. 2014 IEEE Aerospace Conference: Yellowstone Conference Center, Big Sky, Montana, March 1-8, 2014. 2014.Bittner DE. Advances in MEMS IMU Cluster Technology for Small Satellite Advances in MEMS IMU Cluster Technology for Small Satellite Applications Applications. 2015. https://researchrepository.wvu.edu/etdSetter N. Electroceramic-Based MEMS: Fabrication-Technology and Applications (Electronic Materials: Science & Technology). 2005.IEEE Electron Devices Society. The 15th International Conference on Solid-State Sensors, Actuators & Microsystems : Transducers 2009 : Denver, Colorado, U.S.A., June 21-25, 2009, Sheraton Denver Hotel. IEEE Electron Devices Society; 2009.Iniewski K, Ricketts D, Ham D, Morris J, Iannone E. Fundamental Technology and Applications. 2013.Shi LF, Liu H, Liu GX, Zheng F. Body Topology Recognition and Gait Detection Algorithms with Nine-Axial IMMU. IEEE Trans Instrum Meas. 2020; 69(3):721-728. doi:10.1109/TIM.2019.2906969Shi LF, Zhao Y Le, Liu GX, Chen S, Wang Y, Shi YF. A Robust Pedestrian Dead Reckoning System Using Low-Cost Magnetic and Inertial Sensors. IEEE Trans Instrum Meas. 2019;68(8):2996-3003. https://doi.org/10.1109/TIM.2018.2869262Cao Z, Hu L, Yi G, Wang Z. Arm Motion Capture and Recognition Algorithm Based on MEMS Sensor Networks and KPA. In: 2021 International Conference on Electronic Information Engineering and Computer Science, EIECS 2021. Institute of Electrical and Electronics Engineers Inc.; 2021:133-139. https://doi.org/10.1109/EIECS53707.2021.9588046Institute of Electrical and Electronics Engineers, et al. The 2nd IEEE International Symposium on Inertial Sensors and Systems IEEE ISISS 2015: March 23-26, Hawaii, USA; 2015.Leclerc J. MEMs for Aerospace Navigation. IEEE Aerospace and Electronic Systems Magazine. 2007;22(10): 31-36. https://doi.org/10.1109/MAES.2007.4385708Capriglione D, Carratù M, Pietrosanto A, Sommella P, Catelani M, Signorini L. Characterization of Inertial Measurement Units under Environmental Stress Screening. IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia, 2020;1-6. https://doi.org/10.1109/I2MTC43012.2020.9129263Liu S, Liang H, Xiong B. An out-of-plane electromagnetic induction based resonant MEMS magnetometer. Sens Actuators A Phys. 2019;285:248-257. https://doi.org/10.1016/j.sna.2018.11.003Flatau AB, Chong KP. Dynamic Smart Material and Structural Systems. Engineering Structures. 2002;24(3): 261-270. https://doi.org/10.1016/S0141-0296(01)00093-1Fitzgerald AM, Fitzgerald AM. 45 MEMS Inertial Sensors.; 2021.Varadan VK, Vinoy KJ, Gopalakrishnan S. Smart Material Systems and MEMS: Design and Development Methodologies. Wiley; 2006.Barba PDi, Wiak S. MEMS: Field Models and Optimal Design. Lecture Notes in Electrical Engineering 573; 2020.Kraft M, White N (Neil M). MEMS for Automotive and Aerospace Applications. Vol. 556. (Nihtianov S, Luque A, eds.). Woodhead Publishing Limited; 2014.Ananthasuresh GK. Optimal Synthesis Methods for MEMS. Vol. 13. Springer US; 2003. https://doi.org/ 10.1007/978-1-4615-0487-0Azzerboni B, Asti G, Pareti L. Magnetic Nano-structures in Modern Technology. (Ghidini M, ed.). Springer-NATO Science for Peace and Security Series; 2006. http://www.nato.int/scienceShuib S, Ridzwan MIZ, Kadarman AH. Methodology of compliant mechanisms and its current developments in applications: A review. Am J Appl Sci. 2007; 4(3):160-167. https://doi.org/10.3844/ajassp.2007.160.167Kal S., Das S. (2006). Development of silicon and quartz-based MEMS high precision accelerometers. Indian Journal of Pure & Applied Physics, 45, 299-303.Guo D, Wang J, Jia Z, Kang R, Gao H, Wang X. Advances in Materials Manufacturing Science and Technology XIII Volume II.; 2009.Domingue F, Fouladi S, Kouki AB, Mansour RR. Design methodology and optimization of distributed MEMS matching networks for low-microwave-frequency applications. IEEE Trans Microw Theory Tech. 2009; 57(12):3030-3041. https://doi.org/10.1109/TMTT.2009.2034218Krysko VA, Krysko AV, Saltykova OA, Papkova IV. Nonlinear Dynamics of Contact Interaction of MEMS Beam Elements Accounting the Euler-Bernoulli Hypothesis in A Temperature Field. 2017.Nguyen VK, Saltykova OA, Krysko AV. Investigation of nonlinear spatial oscillations of a MEMS beam. Computer science and information technology. Materials of the International Scientific Conference. Saratov: IC Nauka Publ.; 2016:286-288. (In Russ.) EDN: WFWNQVShaeffer DK. MEMS Inertial Sensors: A Tutorial Overview. IEEE Communications Magazine. 2013;51(4): 100-109. https://doi.org/10.1109/MCOM.2013.6495768Khine L, Tsai JM. NEMS/MEMS Technology and Devices. Selected, peer reviewed papers from the International Conference on Materials for Advanced Technologies (ICMAT 2011), Symposium G: NEMS/ MEMS and microTAS, 26 June to 1 July 2011, Suntec, Singapore. 2011. https://doi.org/10.4028/b-3EnkIBChen KS, Ou KS. MEMS residual stress characterization: Methodology and perspective. In: Handbook of Silicon Based MEMS Materials and Technologies. Elsevier; 2020:787-801. https://doi.org/10.1016/B978-0-12-817786-0.00039-6Johnson B, Albrecht C, Braman T, et al. Development of a Navigation-Grade MEMS IMU. In: INERTIAL 2021 - 8th IEEE International Symposium on Inertial Sensors and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc.; 2021. https://doi.org/10.1109/INERTIAL51137.2021.9430466Zhao W, Cheng Y, Zhao S, et al. Navigation grade mems imu for a satellite. Micromachines (Basel). 2021;12(2):1-12. https://doi.org/10.3390/mi12020151Gill WA, Howard I, Mazhar I, McKee K. A Review of MEMS Vibrating Gyroscopes and Their Reliability Issues in Harsh Environments. Sensors. 2022; 22(19). https://doi.org/10.3390/s22197405Hajare R, Reddy V, Srikanth R. MEMS based sensors - A comprehensive review of commonly used fabrication techniques. In: Materials Today: Proceedings. Vol. 49. Elsevier Ltd; 2021:720-730. https://doi.org/10.1016/j.matpr.2021.05.223Goebel R, Tanaka Y, Wahlster W. Autonomous and Intelligent Systems. Third International Conference, AIS 2012, Aviero, Portugal, June 25-27, 2012, Proceedings. Springer Berlin Heidelberg; 2012;283. https://doi.org/10.1007/978-3-642-31368-4Kumar A, Pradeep B, Mallick K, Liu CM, Balas Editors VE. Studies in Computational Intelligence 903 Bio-Inspired Neurocomputing. http://www.springer.com/series/7092Carbonell JG, Siekmann J. Lecture Notes in Artificial Intelligence 3397 Subseries of Lecture Notes in Computer Science; 2004.Fontanella R, Accardo D, Caricati E, Cimmino S, Simone DDe. (2016). An Extensive Analysis for the Use of Back Propagation Neural Networks to Perform the Calibration of MEMS Gyro Bias Thermal Drift. IEEE, 1-9.Xing H, Hou B, Lin Z, Guo M. Modeling and compensation of random drift of MEMS gyroscopes based on least squares support vector machine optimized by chaotic particle swarm optimization. Sensors (Switzerland). 2017;17(10). https://doi.org/10.3390/s17102335Pertin O, Guha K, Jakšić O. Artificial intelligence-based optimization of a bimorph-segmented tapered piezoelectric mems energy harvester for multimode operation. Computation. 2021;9(8). https://doi.org/10.3390/computation9080084Calandra H, Gratton S, Riccietti E, Vasseur X. On a multilevel Levenberg-Marquardt method for the training of artificial neural networks and its application to the solution of partial differential equations. Optim Methods Softw. 2022;37(1):361-386. https://doi.org/10.1080/10556788.2020.1775828Yu H, Wilamowski BM. 2-2 Intelligent Systems; 2011.Abraham A. Meta learning evolutionary artificial neural networks. Neurocomputing. 2004;56(1-4):1-38. https://doi.org/10.1016/S0925-2312(03)00369-2Mohamad N, Zaini F, Johari A, Yassin IM, Zabidi A. Comparison between Levenberg-Marquardt and Scaled Conjugate Gradient Training Algorithms for Breast Cancer Diagnosis using MLP. 6th International Colloquium on Signal Processing & its Applications. Malacca, Malaysia, 2010:162-169. https://doi.org/10.1109/CSPA.2010.5545325Rahmani S, Amjady N. Enhanced goal attainment method for solving multi-objective security-constrained optimal power flow considering dynamic thermal rating of lines. Applied Soft Computing Journal. 2019;77:41-49. https://doi.org/10.1016/j.asoc.2019.01.014Sivanandam SN, Deepa SN. Introduction to Genetic Algorithms. Springer-Verlag Berlin, Heidelberg; 2008. https://doi.org/10.1007/978-3-540-73190-0Sastry K, Goldberg D, Kendall G. Genetic Algorithms: The Design of Innovation. In: Genetic Algorithms: The Design of Innovation. 2nd ed. Springer; 2010:97-125.Haupt RL, Haupt SE. Practical genetic algorithms second edition. 2nd ed. Wiley; 2004.Katoch S, Chauhan SS, Kumar V. A review on genetic algorithm: past, present, and future. Multimed Tools Appl. 2021;80(5):8091-8126. https://doi.org/10.1007/s11042-020-10139-6Alam T, Qamar S, Benaida M. Genetic Algorithm: Reviews, Implementations, and Applications. International Journal of Engineering Pedagogy. 2020. https://doi.org/10.36227/techrxiv.12657173Regassa Hunde B, Debebe Woldeyohannes A. Future prospects of computer-aided design (CAD) - A review from the perspective of artificial intelligence (AI), extended reality, and 3D printing. Results in Engineering. 2022;14. https://doi.org/10.1016/j.rineng.2022.100478Koryagin S, Klachek P, Vasileva V. Development of bionic approaches in the microelectromechanical systems design based on cognitive knowledge bank. 2017 14th International Conference the Experience of Designing and Application of CAD Systems in Microelectronics (CADSM), Lviv, Ukraine, 2017:285-288. https://doi.org/10.1109/CADSM.2017.7916136Institute of Electrical and Electronics Engineers. NAECON 2018 - IEEE National Aerospace and Electronics Conference, Dayton, OH, USA, 2018.Cong L, Yue S, Qin H, Li B, Yao J. Implementation of a MEMS-Based GNSS/INS Integrated Scheme Using Supported Vector Machine for Land Vehicle Navigation. IEEE Sens J. 2020;20(23):14423-14435. https://doi.org/10.1109/JSEN.2020.3007892