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Aerospace
Volume 12
Issue 2
10.3390/aerospace12020104
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Desired Impact Time Range Analysis Using a Deep Neural Network

by
Jiang Wang
1,
Chang Liu
1,
Zichao Liu
1,* and
Peng Huang
2
1
School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
2
Northwest Industries Group Company Ltd., Xi’an 710043, China
*
Author to whom correspondence should be addressed.
Aerospace 2025, 12(2), 104; https://doi.org/10.3390/aerospace12020104
Submission received: 10 January 2025 / Revised: 28 January 2025 / Accepted: 28 January 2025 / Published: 30 January 2025
(This article belongs to the Section Aeronautics)
Versions Notes

Abstract

This paper proposes a desired impact time feasible region estimation model based on a deep neural network. First, a specific multi-constraint guidance law is derived, and the terminal command deviations caused by conventional calculation methods are analyzed. Second, a binary search method is employed to determine the desired impact time range, and samples are collected under various conditions. Next, parameters related to the desired impact time range are analyzed for their sensitivity to identify their influence, thereby improving computational accuracy and reducing sample size. Finally, the accuracy of the proposed method is validated through simulations. Compared with conventional approaches, the DNN-based model demonstrates higher accuracy and provides robust support for simultaneous multi-target engagement.
Keywords: desired impact time range; deep neural network; multi-constraint guidance law; sensitivity analysis; binary search desired impact time range; deep neural network; multi-constraint guidance law; sensitivity analysis; binary search

Share and Cite

MDPI and ACS Style

Wang, J.; Liu, C.; Liu, Z.; Huang, P. Desired Impact Time Range Analysis Using a Deep Neural Network. Aerospace 2025, 12, 104. https://doi.org/10.3390/aerospace12020104

AMA Style

Wang J, Liu C, Liu Z, Huang P. Desired Impact Time Range Analysis Using a Deep Neural Network. Aerospace. 2025; 12(2):104. https://doi.org/10.3390/aerospace12020104

Chicago/Turabian Style

Wang, Jiang, Chang Liu, Zichao Liu, and Peng Huang. 2025. "Desired Impact Time Range Analysis Using a Deep Neural Network" Aerospace 12, no. 2: 104. https://doi.org/10.3390/aerospace12020104

APA Style

Wang, J., Liu, C., Liu, Z., & Huang, P. (2025). Desired Impact Time Range Analysis Using a Deep Neural Network. Aerospace, 12(2), 104. https://doi.org/10.3390/aerospace12020104

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