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On-line Access: 2023-12-26

Received: 2023-02-27

Revision Accepted: 2023-10-09

Crosschecked: 0000-00-00

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

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Article info.

Journal of Zhejiang University SCIENCE A

Accepted manuscript available online (unedited version)


Segmented predictor-corrector reentry guidance based on an analytical profile


Author(s):  Hui XU, Guangbin CAI, Chaoxu MU, Xin LI, Hao WEI

Affiliation(s):  Department of Missile Engineering, Rocket Force University of Engineering, Xi’an 710025, China; more

Corresponding email(s):  cgb0712@163.com

Key Words:  Hypersonic glide vehicle; Segmented reentry guidance method; Analytical profile; Adaptive guidance cycle; Reentry trajectory


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Hui XU, Guangbin CAI, Chaoxu MU, Xin LI, Hao WEI. Segmented predictor-corrector reentry guidance based on an analytical profile[J]. Journal of Zhejiang University Science A,in press.Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/jzus.A2300102

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author="Hui XU, Guangbin CAI, Chaoxu MU, Xin LI, Hao WEI",
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publisher="Zhejiang University Press & Springer",
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%A Xin LI
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Abstract: 
A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance method. Firstly, an altitude-energy profile is designed, and the bank angle is derived analytically as the initial iteration value for the predictor-corrector method. The predictor-corrector guidance method has been improved by deriving an analytical form for predicting the range-to-go error, which greatly accelerates the iterative speed. Then, a segmented guidance algorithm is proposed. The above analytically predictor-corrector guidance method is adopted when the energy exceeds an energy threshold. When the energy is less than the threshold, the equidistant test method is used to calculate the bank angle command, which ensures guidance accuracy as well as computational efficiency. Additionally, an adaptive guidance cycle strategy is applied to reduce the computational time of the reentry guidance trajectory. Finally, the accuracy and robustness of the proposed method are verified through a series of simulations and Monte Carlo experiments. Compared with the traditional integral method, the proposed method requires 75% less computation time on average and achieves a lower landing error.

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