Abstract
With the requirements of high speed, long-range, and large carrying capacity of aircraft in modern flight missions, high-speed aircraft exhibit important research significance in cargo transportation and scientific research. Different from low-speed aircraft, the position, velocity, and acceleration values of high-speed aircraft change very rapidly during flight. Therefore, the navigation problem of high-speed aircraft is a key point that limits its application. In this paper, research results of the Global Navigation Satellite System (GNSS), Inertial Navigation System (INS), and Vision Navigation System (VNS) used to provide navigation information for high-speed aircraft are summarized and compared their advantages and disadvantages. In addition, to achieve more accurate and real-time navigation, the integrated navigation system has become a hot research direction. This paper summarizes the integrated methods based on various traditional navigation methods, such as filtering methods and artificial intelligence-based methods. This paper is expected to provide alternative high-accuracy and easy-to-implement navigation methods for a variety of high-speed aerospace vehicles.
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References
Song, J., Zhao, M., Yang, E., Lin, J.: The high-speed rotorcraft unmanned aerial vehicle path planning based on the biogeography-based optimization algorithm. Adv. Mech. Eng. 11(5), 1–12 (2019)
Barry, A.J., Tedrake, R.: Pushbroom stereo for high-speed navigation in cluttered environments. In: 2015 IEEE International Conference on Robotics and Automation, pp. 3046–3052. IEEE, Seattle, WA, USA (2015)
Huang, C., Zhou, W.: A real-time image matching algorithm for integrated navigation system. Optik 125(16), 4434–4436 (2014)
Yaghi, M., Efe, M.O.: H2/H∞-neural-based FOPID controller applied for radar-guided missile. IEEE Trans. Industr. Electron. 67(6), 4806–4814 (2020)
Lu, Q., Ren, B., Parameswaran, S., Zhong, Q.: Uncertainty and disturbance estimator-based robust trajectory tracking control for a quadrotor in a global positioning system-denied environment. J. Dyn. Syst. Meas. Contr. 140(3), 31001–31016 (2018)
Li, Z., Bai, H., Jin, Y., Liang, H., Wu, D.: Design of integrated navigation algorithm of first sub-stage of launch vehicle. In: Proceedings of the 3rd International Conference on Computer Science and Application Engineering, pp. 1–7. Association for Computing Machinery, Sanya, China (2019)
Hansen, J.M., Fossen, T.I., Johansen, T.A.: Nonlinear observer design for GNSS-aided inertial navigation systems with time-delayed GNSS measurements. Control. Eng. Pract. 60, 39–50 (2017)
Wu, Y., Pan, X.: Velocity/position integration formula Part II: application to strapdown inertial navigation computation. IEEE Trans. Aerosp. Electron. Syst. 49(2), 1024–1034 (2013)
Loquercio, A., Kaufmann, E., Ranftl, R., Dosovitskiy, A., Koltun, V., Scaramuzza, D.: Deep drone racing: from simulation to reality with domain randomization. IEEE Trans. Rob. 36(1), 1–14 (2020)
Wang, Y., Wang, H., Liu, B., Liu, Y., Wu, J., Lu, Z.: A visual navigation framework for the aerial recovery of UAVs. IEEE Trans. Instrum. Meas. 70, 1–13 (2021)
Lu, L., Yunda, A., Carrio, A., Campoy, P.: Robust autonomous flight in cluttered environment using a depth sensor. Int. J. Micro Air Veh. 12, 1–9 (2020)
Abdolkarimi, E.S., Mosavi, M.R.: Wavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system. GPS Solut. 24(2), 1–17 (2020). https://doi.org/10.1007/s10291-020-0951-y
Tian, Y., Xu, H., Jiang, W.: Study on GPS/INS integrated navigation for missile. Space Electr. Technol. 2, 18–24 (2003)
Zhao, G., Shao, W., Chen, K., Yan, J.: Study on UKF based federal integrated navigation for high dynamic aviation. In: International Symposium on Photoelectronic Detection and Imaging 2011: Space Exploration Technologies and Applications, pp. 266–274. SPIE, Beijing, China (2011)
Lazarus, S.B., Tsourdos, A., Silson, P., White, B., Żbikowski, R.: Unmanned aerial vehicle navigation and mapping. Proc. Inst. Mech. Eng. Part G J. Aerosp. Eng. 222(4), 531–548 (2008)
Zou, Z., Huang, T., Ye, L., Song, K.: CNN based adaptive Kalman filter in high-dynamic condition for low-cost navigation system on highspeed UAV. In: 2020 5th Asia-Pacific Conference on Intelligent Robot Systems, pp. 103–108. IEEE, Singapore (2020)
Wang, R., Xiong, Z., Liu, J., Li, R., Peng, H.: SINS/GPS/CNS information fusion system based on improved Huber filter with classified adaptive factors for high-speed UAVs. In: Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium, pp. 441–446. IEEE, Myrtle Beach, SC, USA (2012)
Wang, X., Cui, N., Guo, J.: INS/VisNav/GPS relative navigation system for UAV. Aerosp. Sci. Technol. 28(1), 242–248 (2013)
Jiang, X., Yu, J., Zhu, L.: Research of combined navigation technology based on position sensitive detectors. Laser Technol. 43(3), 335–340 (2019)
Malleswaran, M., Vaidehi, V., Sivasankari, N.: A novel approach to the integration of GPS and INS using recurrent neural networks with evolutionary optimization techniques. Aerosp. Sci. Technol. 32(1), 169–179 (2014)
Abdolkarimi, E.S., Abaei, G., Mosavi, M.R.: A wavelet-extreme learning machine for low-cost INS/GPS navigation system in high-speed applications. GPS Soluti. 22(1), 1–13 (2017). https://doi.org/10.1007/s10291-017-0682-x
Acknowledgments
This work was supported in part by the National Science Foundation of China under Grant 12072027, in part by the National Science Foundation of China under Grant 62103052, and in part by the Open Research Project of The Beijing Key Laboratory of High Dynamic Navigation Technology under grant No. HDN2021101.
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Cheng, Z., Zhao, L. (2023). A Review on Navigation Methods for High-Speed Aircraft. In: Yan, L., Duan, H., Deng, Y. (eds) Advances in Guidance, Navigation and Control. ICGNC 2022. Lecture Notes in Electrical Engineering, vol 845. Springer, Singapore. https://doi.org/10.1007/978-981-19-6613-2_298
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DOI: https://doi.org/10.1007/978-981-19-6613-2_298
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