Abstract
This paper focuses on the analysis of the desired impact time range under multiple constraints. In order to solve the problem that the precision of the traditional formula method is not high enough to calculate the time range, this paper proposes, for the first time, the application of a BP neural network to address the problem, thereby mitigating the failure of the salvo attack. First, a specific guidance law with multiple constraints was selected, and it was demonstrated that the desired impact time range cannot be accurately solved by the traditional formula method, which leads to miss. Secondly, analyzed the parameters that affected the guidance time range, and carried out sensitivity analysis on them, so as to obtain the influence degree of each parameter on the range, and reduced the sample size while ensuring accuracy. Then, the binary search method was applied to obtain the impact time range, in order to obtain the samples. After obtained the samples, the BP neural network was used to train the samples. Finally, the accuracy of this method was verified by simulation, which provided an important premise for salvo attacks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jeon, I.S., Lee, J.I., Tahk, M.J.: Impact-time-control guidance law for anti-ship missiles. IEEE Trans. Control Syst. Technol. 14(2), 260–266 (2006)
Shiyu, Z., Rui, Z.: Cooperative guidance for multimissile salvo attack. Chin. J. Aeronaut. 21(6), 533–539 (2008)
Kim, M., Jung, B., Han, B., et al.: Lyapunov-based impact time control guidance laws against stationary targets. IEEE Trans. Aerosp. Electron. Syst. 51(2), 1111–1122 (2015)
Jeon, I.S., Lee, J.I., Tahk, M.J.: Impact-time-control guidance with generalized proportional navigation based on nonlinear formulation. J. Guid. Control. Dyn. 39(8), 1885–1890 (2016)
Dong, W., Wang, C., Wang, J., et al.: Three-dimensional nonsingular cooperative guidance law with different field-of-view constraints. J. Guid. Control. Dyn. 44(11), 2001–2015 (2021)
Zhang, Y., Wang, X., Wu, H.: Impact time control guidance law with field of view constraint. Aerosp. Sci. Technol. 39, 361–369 (2014)
Lee, S., Cho, N., Kim, Y.: Impact-time-control guidance strategy with a composite structure considering the seeker’s field-of-view constraint. J. Guid. Control. Dyn. 43(8), 1566–1574 (2020)
Jeon, I.S., Lee, J.I.: Impact-time-control guidance law with constraints on seeker look angle. IEEE Trans. Aerosp. Electron. Syst. 53(5), 2621–2627 (2017)
Chen, Y., Wang, J., Wang, C., et al.: Three-dimensional cooperative homing guidance law with field-of-view constraint. J. Guid. Control. Dyn. 43(2), 389–397 (2020)
Shaoming, H.E., Chang-Hun, L.E.E., Hyo-Sang, S., et al.: Optimal three-dimensional impact time guidance with seeker’s field-of-view constraint. Chin. J. Aeronaut. 34(2), 240–251 (2021)
Liu, Z., Wang, J., He, S., et al.: Learning prediction-correction guidance for impact time control. Aerosp. Sci. Technol. 119, 107187 (2021)
Shi, Y., Wang, Z.: A deep learning-based approach to real-time trajectory optimization for hypersonic vehicles. AIAA SciTech 2020 forum (0023)
Cheng, L., Jiang, F., Wang, Z., et al.: Multi-constrained real-time entry guidance using deep neural networks. IEEE Trans. Aerosp. Electron. Syst. 57(1), 325–340 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 Chinese Institute of Command and Control
About this paper
Cite this paper
Liu, C., Fan, W., Li, J., Zhu, Z. (2024). Desired Impact Time Range Based on BP Neural Network. In: Chinese Institute of Command and Control (eds) Proceedings of 2023 11th China Conference on Command and Control. C2 2023. Lecture Notes in Electrical Engineering, vol 1124. Springer, Singapore. https://doi.org/10.1007/978-981-99-9021-4_17
Download citation
DOI: https://doi.org/10.1007/978-981-99-9021-4_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-9020-7
Online ISBN: 978-981-99-9021-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)