Abstract
Artificial Intelligence (AI) is a branch of computer science, created by humans to help computers to automate intelligent behaviors and have human-like intelligence. Currently, AI is a spearhead technology with potential applications in many areas of social life. In particular, in the military, AI is being developed more and more perfectly and started to be applied in practice. This paper proposes a method of applying an artificial neural network to compensate for the lost GNSS signal in the loosely coupled structure to improve the accuracy of the positioning and navigation process for a class of flying devices. The obtained results proved the correctness of the indicated method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Niu, M., Ma, H., Sun, X., Huang, T., Song, K.: A new self-calibration and compensation method for installation errors of uniaxial rotation module inertial navigation system. Sensors 22, 3812 (2022). https://doi.org/10.3390/s22103812
Khatab, E., Onsy, A., Abouelfarag, A.: Evaluation of 3D vulnerable objects’ detection using a multi-sensors system for autonomous vehicles. Sensors 22, 1663 (2022). https://doi.org/10.3390/s22041663
Muraleedharan, N., Cohen, D.S., Estrela, V.V., Hemanth, J., Saotome, O., Nikolakopoulos, G., Sabatini, R., Wackett, L.: Modelling and simulation of UAV systems. In: Estrela, V.V., Hemanth, J., Saotome, O., Nikolakopoulos, G., and Sabatini, R. (eds.): Imaging and Sensing for Unmanned Aircraft Systems. Volume 1: Control and Performance, pp. 101–121. Institution of Engineering and Technology (2020). https://doi.org/10.1049/PBCE120F_ch5
Skog, Händel, P.: A low-cost GPS aided inertial navigation system for vehicle applications. In: 2005 13th European Signal Processing Conference, Antalya, Turkey, pp. 1–4 (2005)
Shin, E.-H.: Estimation techniques for low-cost inertial navigation. UCGE report, 20219 (2005)
Van, T.P., Van, T.N., Nguyen, D.A., Duc, T.C., Duc, T.T.: 15-state extended Kalman filter design for INS/GPS navigation system. JOACE 3, 109–114 (2015). https://doi.org/10.12720/joace.3.2.109-114
Zheng, T., Xu, A., Xu, X., Liu, M.: Modeling and compensation of inertial sensor errors in measurement systems. Electronics 12, 2458 (2023). https://doi.org/10.3390/electronics12112458
Skog, I., Händel, P.: Calibration of a MEMS inertial measurement unit. In: XVII IMEKO World Congress, pp. 1–6 (2006)
Mok, E., Retscher, G., Wen, C.: Initial test on the use of GPS and sensor data of modern smartphones for vehicle tracking in dense high rise environments. In: 2012 Ubiquitous Positioning, Indoor Navigation, and Location Based Service (UPINLBS). pp. 1–7. IEEE, Helsinki, Finland (2012). https://doi.org/10.1109/UPINLBS.2012.6409789
Guerrero-Castellanos, J.F., Madrigal-Sastre, H., Durand, S., Marchand, N., Guerrero-Sanchez, W.F., Salmeron, B.B.: Design and implementation of an attitude and heading reference system (AHRS). In: 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, pp. 1–5. IEEE, Merida City, Mexico (2011). https://doi.org/10.1109/ICEEE.2011.6106610
Vinh, N.Q.: INS/GPS integration system using street return algorithm and compass sensor. Procedia Comput. Sci. 103, 475–482 (2017). https://doi.org/10.1016/j.procs.2017.01.030
Vinh, N.Q., Thoa, P.D.: Improving high quality in combination processing the high-measurement signals. In: Satapathy, S.C., Bhateja, V., Nguyen, B.L., Nguyen, N.G., and Le, D.-N. (eds.) Frontiers in Intelligent Computing: Theory and Applications, pp. 328–340. Springer Singapore, Singapore (2020). https://doi.org/10.1007/978-981-32-9186-7_34
Kubat, M.: Neural networks: a comprehensive foundation by Simon Haykin, Macmillan, 1994, ISBN 0–02–352781–7. Knowl. Eng. Rev. 13(4):409–412 (1999)
Jaakkola, H., Thalheim, B., Henno, J.: About the essence of intelligence—will artificial intelligence (ever) cover human intelligence? In: Tropmann-Frick, M., Jaakkola, H., Thalheim, B., Kiyoki, Y., Yoshida, N. (eds.) Frontiers in Artificial Intelligence and Applications. IOS Press (2022). https://doi.org/10.3233/FAIA210475
Karaboga, D., Kaya, E.: Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey. Artif. Intell. Rev. Intell. Rev. 52, 2263–2293 (2019). https://doi.org/10.1007/s10462-017-9610-2
Tamilselvi, S.: Introduction to evolutionary algorithms. In: Ventura, S., MarÃa Luna, J., MarÃa Moyano, J. (eds.) Genetic Algorithms. IntechOpen (2022). https://doi.org/10.5772/intechopen.104198
Rajan, H.: An Experiential Introduction to Principles of Programming Languages. MIT Press (2022)
Introduction to Genetic Algorithms. Springer Berlin Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-73190-0
Tetko, I.V., Kůrková, V., Karpov, P., Theis, F. (eds.): Artificial Neural Networks and Machine Learning—ICANN 2019: Image Processing: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III. Springer International Publishing, Cham (2019). https://doi.org/10.1007/978-3-030-30508-6
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Tran, D.T., Nguyen, V.Q., Nguyen, C.V., Tran, D.L.T., Tran, H.T., Anh, N.D. (2023). Improved Accuracy of Path System on Creating Intelligence Base. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2023. Lecture Notes in Networks and Systems, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-031-49529-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-49529-8_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-49528-1
Online ISBN: 978-3-031-49529-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)