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Journal articles on the topic 'Hypersonic glide vehicles'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Cheng, Yunpeng, Xiaodong Yan, and Feng Cheng. "Trajectory Estimation of Hypersonic Glide Vehicle Based on Analysis of Aerodynamic Performance." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, no. 6 (December 2019): 1102–10. http://dx.doi.org/10.1051/jnwpu/20193761102.

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Due to high speed and high maneuverability of hypersonic glide vehicles (HGVs), the state estimation of such targets has always been a research hotspot. In order to improve accuracy of the trajectory estimation, a nonlinear aerodynamic parameter model for target estimation based on aerodynamic performance analysis is proposed. Firstly, the dynamic characteristics of the hypersonic glide vehicle during the hypersonic gliding stage was analyzed. Then, aiming at HTV-2-liked vehicle, the engineering calculation method was used to form the reference aerodynamic model for the target estimation. Secondly, a deviation model described by first-order Markov process was introduced to compensate the uncertainties of the unknown maneuver information from the target. Finally, extended Kalman filter was utilized to estimate the state of the target. The simulation results show that the proposed model is able to improve the accuracy of acceleration estimation for the HTV-2-liked hypersonic gliding vehicles.

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2

Chen, Kai, Fuqiang Shen, Jun Zhou, and Xiaofeng Wu. "SINS/BDS Integrated Navigation for Hypersonic Boost-Glide Vehicles in the Launch-Centered Inertial Frame." Mathematical Problems in Engineering 2020 (November 12, 2020): 1–16. http://dx.doi.org/10.1155/2020/7503272.

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According to the trajectory specialty of hypersonic boost-glide vehicles, a strapdown inertial navigation system/BeiDou navigation satellite system (SINS/BDS) algorithm based on the launch-centered inertial (LCI) frame for hypersonic vehicles is proposed. First, the related frame system, especially the launch earth-centered inertial (LECI) frame, and the SINS mechanization in the LCI frame are introduced. Second, SINS discrete updating algorithms in the LCI frame for the compensation of coning, sculling, and scrolling effects are deduced in the attitude, velocity, and position updating algorithms, respectively. Subsequently, the Kalman filter of the SINS/BDS integrated navigation in the LCI frame is obtained. The method of converting BDS receiver position and velocity from the Earth-centered Earth-fixed (ECEF) frame to the LCI frame is deduced through the LECI frame. Finally, taking the typical hypersonic boost-glide vehicles as the object, the SINS/BDS algorithm vehicle field test and hardware-in-the-loop simulation are performed.

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3

Yan, Xiaodong, Shi Lyu, and Shuo Tang. "Analysis of optimal initial glide conditions for hypersonic glide vehicles." Chinese Journal of Aeronautics 27, no. 2 (April 2014): 217–25. http://dx.doi.org/10.1016/j.cja.2014.02.019.

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4

Li, Guanghua, Hongbo Zhang, and Guojian Tang. "Flight-Corridor Analysis for Hypersonic Glide Vehicles." Journal of Aerospace Engineering 30, no. 1 (January 2017): 06016005. http://dx.doi.org/10.1061/(asce)as.1943-5525.0000667.

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5

Zhu, Jianwen, Ruizhi He, Guojian Tang, and Weimin Bao. "Pendulum maneuvering strategy for hypersonic glide vehicles." Aerospace Science and Technology 78 (July 2018): 62–70. http://dx.doi.org/10.1016/j.ast.2018.03.038.

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6

Li, Guanghua, Hongbo Zhang, and Guojian Tang. "Maneuver characteristics analysis for hypersonic glide vehicles." Aerospace Science and Technology 43 (June 2015): 321–28. http://dx.doi.org/10.1016/j.ast.2015.03.016.

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7

Xu, MingLiang, KeJun Chen, LuHua Liu, and GuoJian Tang. "Quasi-equilibrium glide adaptive guidance for hypersonic vehicles." Science China Technological Sciences 55, no. 3 (January 16, 2012): 856–66. http://dx.doi.org/10.1007/s11431-011-4727-z.

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8

Hu, Yudong, Changsheng Gao, Junlong Li, and Wuxing Jing. "Maneuver mode analysis and parametric modeling for hypersonic glide vehicles." Aerospace Science and Technology 119 (December 2021): 107166. http://dx.doi.org/10.1016/j.ast.2021.107166.

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9

Meng, Fanqing, and Kangsheng Tian. "Phased-Array Radar Task Scheduling Method for Hypersonic-Glide Vehicles." IEEE Access 8 (2020): 221288–98. http://dx.doi.org/10.1109/access.2020.3043338.

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10

Zhou, Hongyu, Xiaogang Wang, and Naigang Cui. "Glide trajectory optimization for hypersonic vehicles via dynamic pressure control." Acta Astronautica 164 (November 2019): 376–86. http://dx.doi.org/10.1016/j.actaastro.2019.08.012.

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11

Hu, Yudong, Changsheng Gao, and Wuxing Jing. "Joint State and Parameter Estimation for Hypersonic Glide Vehicles Based on Moving Horizon Estimation via Carleman Linearization." Aerospace 9, no. 4 (April 14, 2022): 217. http://dx.doi.org/10.3390/aerospace9040217.

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Aimed at joint state and parameter estimation problems in hypersonic glide vehicle defense, a novel moving horizon estimation algorithm via Carleman linearization is developed in this paper. First, the maneuver characteristic parameters that reflect the target maneuver law are extended into the state vector, and a dynamic tracking model applicable to various hypersonic glide vehicles is constructed. To improve the estimation accuracy, constraints such as path and parameter change amplitude constraints in flight are taken into account, and the estimation problem is transformed into a nonlinear constrained optimal estimation problem. Then, to solve the problem of high time cost for solving a nonlinear constrained optimal estimation problem, in the framework of moving horizon estimation, nonlinear constrained optimization problems are transformed into bilinear constrained optimization problems by linearizing the nonlinear system via Carleman linearization. For ensuring the consistency of the linearized system with the original nonlinear system, the linearized model is continuously updated as the window slides forward. Moreover, a CKF-based arrival cost update algorithm is also provided to improve the estimation accuracy. Simulation results demonstrate that the proposed joint state and parameter estimation algorithm greatly improves the estimation accuracy while reducing the time cost significantly.

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12

Kessler, Alexander. "Russian Hypersonic Glide Vehicles: What to Know and What to Fear." Orbis 66, no. 2 (2022): 213–23. http://dx.doi.org/10.1016/j.orbis.2022.02.009.

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13

Chen, Kai, Sensen Pei, Fuqiang Shen, and Shangbo Liu. "Tightly Coupled Integrated Navigation Algorithm for Hypersonic Boost-Glide Vehicles in the LCEF Frame." Aerospace 8, no. 5 (April 23, 2021): 124. http://dx.doi.org/10.3390/aerospace8050124.

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According to the trajectory characteristics of hypersonic boost-glide vehicles, a tightly coupled integrated navigation algorithm for hypersonic vehicles based on the launch-centered Earth-fixed (LCEF) frame is proposed. First, the strapdown inertial navigation mechanization algorithm and discrete update algorithm in the LCEF frame are introduced. Subsequently, the attitude, velocity, and position error equations of strapdown inertial navigation in the LCEF frame are introduced. The strapdown inertial navigation system/global positioning system (SINS/GPS) pseudo-range and pseudo-range rate measurement equations in the LCEF frame are derived. Further, the tightly coupled SINS/GPS integrated navigation filter state equation and the measurement equation are presented. Finally, the tightly coupled SINS/GPS integrated navigation algorithm is verified in the hardware-in-the-loop (HWIL) simulation environment. The simulation results indicate that the precision of tightly coupled integrated navigation is better than that of loosely coupled integrated navigation. Moreover, even when the number of effective satellites is less than four, tightly coupled integrated navigation functions well, thus verifying the effectiveness and feasibility of the algorithm.

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14

Williams, Heather. "Asymmetric arms control and strategic stability: Scenarios for limiting hypersonic glide vehicles." Journal of Strategic Studies 42, no. 6 (August 22, 2019): 789–813. http://dx.doi.org/10.1080/01402390.2019.1627521.

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15

Liu, Xinfu, and Zuojun Shen. "Rapid Smooth Entry Trajectory Planning for High Lift/Drag Hypersonic Glide Vehicles." Journal of Optimization Theory and Applications 168, no. 3 (October 30, 2015): 917–43. http://dx.doi.org/10.1007/s10957-015-0831-8.

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16

He, Rui-Zhi, Yuan-Long Zhang, Lu-Lua Liu, Guo-Jian Tang, and Wei-Min Bao. "Feasible footprint generation with uncertainty effects." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 1 (August 31, 2017): 138–50. http://dx.doi.org/10.1177/0954410017728971.

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Landing footprint is critical in generating feasible entry trajectories for hypersonic glide vehicles. In this paper, a new landing footprint generation algorithm that considers multiple uncertainty effects is proposed, based on the improved 3D acceleration profile planning method. First, a new entry corridor with uncertainty effects is derived, in which the angle of attack profile is adjustable at any time during the entire flight. Second, the longitudinal drag profile is designed as the interpolation results of the upper and lower fitting safe boundaries. The corresponding lateral lift-to-drag corridor is obtained using the quasi-equilibrium glide condition. A combined Proportion Integration Differentiation (PID) tracker is used to follow the planned profiles in the longitudinal and lateral corridors, and the feasible entry trajectories are completed. Finally, feasible footprint is generated by repeatedly computing the reachable boundaries for all the profiles in the new safe corridor, as well as the analytical calculation of the maximum range point. The approach is tested using the Common Aero Vehicle-H model. Simulation results demonstrate that the proposed algorithm can rapidly generate a feasible footprint of entry for vehicles while satisfying all the path and terminal constraints.

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17

Xu, Jingjing, Changhong Dong, and Lin Cheng. "Deep Neural Network-Based Footprint Prediction and Attack Intention Inference of Hypersonic Glide Vehicles." Mathematics 11, no. 1 (December 29, 2022): 185. http://dx.doi.org/10.3390/math11010185.

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In response to the increasing threat of hypersonic weapons, it is of great importance for the defensive side to achieve fast prediction of their feasible attack domain and online inference of their most probable targets. In this study, an online footprint prediction and attack intention inference algorithm for hypersonic glide vehicles (HGVs) is proposed by leveraging the utilization of deep neural networks (DNNs). Specifically, this study focuses on the following three contributions. First, a baseline multi-constrained entry guidance algorithm is developed based on a compound bank angle corridor, and then a dataset containing enough trajectories for the following DNN learning is generated offline by traversing different initial states and control commands. Second, DNNs are developed to learn the functional relationship between the flight state/command and the corresponding ranges; on this basis, an online footprint prediction algorithm is developed by traversing the maximum/minimum ranges and different heading angles. Due to the substitution of DNNs for multiple times of trajectory integration, the computational efficiency for footprint prediction is significantly improved to the millisecond level. Third, combined with the predicted footprint and the hidden information in historical flight data, the attack intention and most probable targets can be further inferred. Simulations are conducted through comparing with the state-of-the-art algorithms, and results demonstrate that the proposed algorithm can achieve accurate prediction for flight footprint and attack intention while possessing significant real-time advantage.

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18

Wang, Ziyao, Shengjing Tang, and Jie Guo. "Entry Guidance Command Generation for Hypersonic Glide Vehicles Under Threats and Multiple Constraints." IEEE Access 10 (2022): 1–15. http://dx.doi.org/10.1109/access.2021.3137641.

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19

Zhang, Bin, Zhiwei Feng, Boting Xu, and Tao Yang. "Free Form Deformation Method Applied to Modeling and Design of Hypersonic Glide Vehicles." IEEE Access 7 (2019): 61400–61413. http://dx.doi.org/10.1109/access.2019.2915516.

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20

Wang, Zhenbo. "Optimal trajectories and normal load analysis of hypersonic glide vehicles via convex optimization." Aerospace Science and Technology 87 (April 2019): 357–68. http://dx.doi.org/10.1016/j.ast.2019.03.002.

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21

Chen, Si-Yuan, and Qun-Li Xia. "A Multiconstrained Ascent Guidance Method for Solid Rocket-Powered Launch Vehicles." International Journal of Aerospace Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/6346742.

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This study proposes a multiconstrained ascent guidance method for a solid rocket-powered launch vehicle, which uses a hypersonic glide vehicle (HGV) as payload and shuts off by fuel exhaustion. First, pseudospectral method is used to analyze the two-stage launch vehicle ascent trajectory with different rocket ignition modes. Then, constraints, such as terminal height, velocity, flight path angle, and angle of attack, are converted into the constraints within height-time profile according to the second-stage rocket flight characteristics. The closed-loop guidance method is inferred by different spline curves given the different terminal constraints. Afterwards, a thrust bias energy management strategy is proposed to waste the excess energy of the solid rocket. Finally, the proposed method is verified through nominal and dispersion simulations. The simulation results show excellent applicability and robustness of this method, which can provide a valuable reference for the ascent guidance of solid rocket-powered launch vehicles.

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22

Cheng, Yunpeng, Xiaodong Yan, Shuo Tang, Manqiao Wu, and Chaoyong Li. "An adaptive non-zero mean damping model for trajectory tracking of hypersonic glide vehicles." Aerospace Science and Technology 111 (April 2021): 106529. http://dx.doi.org/10.1016/j.ast.2021.106529.

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23

Li, Zhenhua, Chen Hu, Chibiao Ding, Gang Liu, and Bing He. "Stochastic gradient particle swarm optimization based entry trajectory rapid planning for hypersonic glide vehicles." Aerospace Science and Technology 76 (May 2018): 176–86. http://dx.doi.org/10.1016/j.ast.2018.01.033.

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24

Yan, Xunliang, Peichen Wang, Shaokang Xu, Shumei Wang, and Hao Jiang. "Adaptive Entry Guidance for Hypersonic Gliding Vehicles Using Analytic Feedback Control." International Journal of Aerospace Engineering 2020 (November 17, 2020): 1–18. http://dx.doi.org/10.1155/2020/8874251.

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This paper presents an adaptive, simple, and effective guidance approach for hypersonic entry vehicles with high lift-to-drag (L/D) ratios (e.g., hypersonic gliding vehicles). The core of the constrained guidance approach is a closed-form, easily obtained, and computationally efficient feedback control law that yields the analytic bank command based on the well-known quasi-equilibrium glide condition (QEGC). The magnitude of the bank angle command consists of two parts, i.e., the baseline part and the augmented part, which are calculated analytically and successively. The baseline command is derived from the analytic relation between the range-to-go and the velocity to guarantee the range requirement. Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. The inequality path constraints in the velocity-altitude space are translated into the velocity-dependent bounds for the magnitude of the bank angle based on the QEGC. The sign of the bank command is also analytically determined using an automated bank-reversal logic based on the dynamic adjustment criteria. Finally, a feasible three-degree-of-freedom (3DOF) entry flight trajectory is simultaneously generated by integrating with the real-time updated command. Because no iterations and no or few off-line parameter adjustments are required using almost all analytic processing, the algorithm provides remarkable simplicity, rapidity, and adaptability. A considerable range of entry flights using the vehicle data of the CAV-H is tested. Simulation results demonstrate the effectiveness and performance of the presented approach.

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25

Kumar, G. Naresh, AK Sarkar, KK Mangrulkar, and SE Talole. "Atmospheric vehicle trajectory optimization with minimum dynamic pressure constraint." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 5 (April 30, 2017): 837–46. http://dx.doi.org/10.1177/0954410017699436.

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In this work, a trajectory optimization formulation for hypersonic boost–glide class vehicles to achieve maximum range under various in-flight and terminal constraints is proposed. While most of the published literature has considered maximum dynamic pressure as a constraint, the requirement of a certain minimum dynamic pressure has been addressed in this formulation to ensure aerodynamic controllability throughout the flight envelope for various ranges. The minimum dynamic pressure constraint is imposed as an in-flight inequality constraint and is achieved through a penalty function approach by casting it as a differential equation. Simulations are carried out, and the results are analyzed and presented to demonstrate the efficacy of the proposed formulation.

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26

Meng, Fanqing, and Kangsheng Tian. "Interval type-2 fuzzy logic based radar task priority assignment method for detecting hypersonic-glide vehicles." Frontiers of Information Technology & Electronic Engineering 23, no. 3 (February 5, 2022): 488–501. http://dx.doi.org/10.1631/fitee.2000560.

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27

Cheng, Yu, Cheng Wei, Yongshang Wei, Bindi You, and Yang Zhao. "Intention Prediction of a Hypersonic Glide Vehicle Using a Satellite Constellation Based on Deep Learning." Mathematics 10, no. 20 (October 12, 2022): 3754. http://dx.doi.org/10.3390/math10203754.

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Tracking of hypersonic glide vehicles (HGVs) by a constellation tracking and observation system is an important part of the space-based early warning system. The uncertainty in the maneuver intentions of HGVs has a non-negligible impact on the tracking and observation process. The cooperative scheduling of multiple satellites in an environment of uncertainty in the maneuver intentions of HGVs is the main problem researched in this paper. For this problem, a satellite constellation tracking decision method that considers the HGVs’ maneuver intentions is proposed. This method is based on building an HGV maneuver intention model, developing a maneuver intention recognition and prediction algorithm, and designing a sensor-switching strategy to improve the local consensus-based bundle algorithm (LCBBA). Firstly, a recognizable maneuver intention model that can describe the maneuver types and directions of the HGVs in both the longitudinal and lateral directions was designed. Secondly, a maneuver intention recognition and prediction algorithm based on parallel, stacked long short-term memory neural networks (PSLSTM) was developed to obtain maneuver directions of the HGV. On the basis of that, a satellite constellation tracking decision method (referred to as SS-LCBBA in the following) considering the HGVs’ maneuver intentions was designed. Finally, the maneuver intention prediction capability of the PSLSTM network and two currently popular network structures: the multilayer LSTM (M-LSTM) and the dual-channel and bidirectional neural network (DCBNN) were tested for comparison. The simulation results show that the PSLSTM can recognize and predict the maneuver directions of HGVs with high accuracy. In the simulation of a satellite constellation tracking HGVs, the SS-LCBBA improved the cumulative tracking score compared to the LCBBA, the blackboard algorithm (BM), and the variable-center contract network algorithm (ICNP). Thus, it is concluded that SS-LCBBA has better adaptability to environments with uncertain intentions in solving multi-satellite collaborative scheduling problems.

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28

Song, Jia, Xindi Tong, Xiaowei Xu, and Kai Zhao. "A Real-Time Reentry Guidance Method for Hypersonic Vehicles Based on a Time2vec and Transformer Network." Aerospace 9, no. 8 (August 4, 2022): 427. http://dx.doi.org/10.3390/aerospace9080427.

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In this paper, a real-time reentry guidance law for hypersonic vehicles is presented to accomplish rapid, high-precision, robust, and reliable reentry flights by leveraging the Time to Vector (Time2vec) and transformer networks. First, referring to the traditional predictor–corrector algorithm and quasi-equilibrium glide condition (QEGC), the reentry guidance issue is described as a univariate root-finding problem based on bank angle. Second, considering that reentry guidance is a sequential decision-making process, and its data has inherent characteristics in time series, so the Time2vec and transformer networks are trained to obtain the mapping relation between the flight states and bank angles, and the inputs and outputs are specially designed to guarantee that the constraints can be well satisfied. Based on the Time2vec and transformer-based bank angle predictor, an efficient and precise reentry guidance approach is proposed to realize on-line trajectory planning. Simulations and analysis are carried out through comparison with the traditional predictor-corrector algorithm, and the results manifest that the developed Time2vec and transformer-based reentry guidance algorithm has remarkable improvements in accuracy and efficiency under initial state errors and aerodynamic parameter perturbations.

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29

Bushnell, D. M. "The ‘air side’ of future warfare – military aeronautics." Aeronautical Journal 107, no. 1072 (June 2003): 301–5. http://dx.doi.org/10.1017/s0001924000013592.

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Abstract The ongoing revolutions in information, biological, energetics and nano technologies are changing the nature and equipment of warfare. This is particularly true in military aeronautics. In the nearer term aircraft are becoming increasingly ‘uninhabited’ (UCAVs, UAVs etc.) enabled by the IT revolution, with multitudinous accompanying benefits in terms of affordability, survivability, redefinition of ‘risk’ and lethality. THE issue for such aircraft is enhanced persistence and increased range within the context of the overall system metrics. In the longer term the increasingly capable worldwide ‘sensor web’ will place at risk all air vehicles, in or out of theatre and whether or not they are ‘stealthy’. This, combined with advanced conventional weapons, high energy density material powered EMP (electro-magnetic-pulse) weapons and affordable swarms of ‘brilliant’ munitions will probably require yet another re-definition of military aeronautics, perhaps as survivable (hardened) hypersonic, global range, boost-glide devices.

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30

Prasad Singh, Hanuman. "ARTIFICIAL INTELLIGENCE AFFECTING STRATEGIC STABILITY." International Journal of Advanced Research 10, no. 03 (March 31, 2022): 01–04. http://dx.doi.org/10.21474/ijar01/14356.

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Introduction of artificial intelligence(AI) in the nuclear weapons system exerts the stabilizing as well as destabilizing effect on strategic stability. AI enables informed decision making, development of more survivable delivery vehicle, physical and cyber security of nuclear assets, reduction in possibility of human error, surveillance of compliance of non-proliferation and disarmament treaties, integration of heterogeneous weapons for better performance, and underwater de-mining, etc. Simultaneously, by contrast, the threat to nuclear deterrence and nuclear assets from hypersonic glide vehicle leading to capability race, remote sensing over autonomous surface and underwater vehicles threatening invulnerable second strike capability, Patrov incident like situations possibility and requirement of human interference, instability inherent in threat detection with the deployment of AI driven more survivable and less controllable platforms including UCAVs, UAVs, UUVs, SLBMs, etc. are threatening the strategic stability. Which must be mitigated for long-lasting global peace through the development of universally accepted code of conduct in line with 1949 Geneva convention and Universal declaration of human rights 1948, etc, deliberation for risk reduction in regional as well as global stages, track two and 1.5 diplomacy, enabling human intervention in nuclear weapon launch system, commitment for No first use policy, complex interdependence etc.

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31

Zhao, Jiang, Rui Zhou, and Xuelian Jin. "Reentry Trajectory Optimization Based on a Multistage Pseudospectral Method." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/878193.

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Of the many direct numerical methods, the pseudospectral method serves as an effective tool to solve the reentry trajectory optimization for hypersonic vehicles. However, the traditional pseudospectral method is time-consuming due to large number of discretization points. For the purpose of autonomous and adaptive reentry guidance, the research herein presents a multistage trajectory control strategy based on the pseudospectral method, capable of dealing with the unexpected situations in reentry flight. The strategy typically includes two subproblems: the trajectory estimation and trajectory refining. In each processing stage, the proposed method generates a specified range of trajectory with the transition of the flight state. The full glide trajectory consists of several optimal trajectory sequences. The newly focused geographic constraints in actual flight are discussed thereafter. Numerical examples of free-space flight, target transition flight, and threat avoidance flight are used to show the feasible application of multistage pseudospectral method in reentry trajectory optimization.

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32

Zvedre, E. "Does the US program of Conventional Prompt Global Strike threaten Russian national security?" Journal of International Analytics, no. 1 (March 28, 2016): 52–61. http://dx.doi.org/10.46272/2587-8476-2016-0-1-52-61.

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The article analyses a concept of Conventional Prompt Global Strike aimed at developing weapons systems that can deliver a conventional warhead anywhere in the world within an hour as a prioritized part of the US military strategy. The Pentagon planners believe that deployment of CPGS weapon would allow a selective and far more effective response to post-cold war threats, such as international terrorist networks, “rogue states” and other adversaries, thus drastically reducing reliance on nuclear deterrent in a number of situations. Over the years the Pentagon’s R&D activities in this area encompassed numerous established and emerging weapon technologies, including use of surface-launched and sea-launched strategic missiles and hypersonic glide vehicles. The CPGS program is raising serious concerns in Moscow, where Russian officials consider it as a threat to Russia’s strategic nuclear arsenals and national security interests alongside with the US plans to develop and deploy global ballistic missile defense capabilities and attack weapons in space. Moscow predicts it could undermine strategic balance and trigger a nonnuclear arms race.

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33

Xu Hui, 徐慧, 蔡光斌 Cai Guangbin, 穆朝絮 Mu Chaoxu, 张艳红 Zhang Yanhong, and 李欣 Li Xin. "高超声速滑翔飞行器全程总红外辐射最小的轨迹优化（特邀）." Infrared and Laser Engineering 51, no. 4 (2022): 20220194. http://dx.doi.org/10.3788/irla20220194.

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34

Zhang, Ke Nan, and Wan Chun Chen. "Trajectory Optimization for Hypersonic Vehicle Satisfying Maneuvering Penetration." Applied Mechanics and Materials 110-116 (October 2011): 5223–31. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.5223.

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A trajectory optimization method for hypersonic vehicle in glide phase satisfying maneuvering penetration is proposed. Divide the dangerous zones that the hypersonic vehicle may encounter during glide phase into avoidable no-fly zones and avoidless no-fly zones. Take the avoidable no-fly zones as path constraints to join the trajectory optimization. To penetrate the avoidless no-fly zones, trajectory is programmed by some maneuvering policy. Direct shooting method is used to discretize the control variable to piecewise constant functions. So the optimal control problem is transferred to a nonlinear programming (NLP) problem, and solved by the serial quadratic program (SQP) method.

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35

Rizvi, S. T. I., H. Linshu, X. Dajun, and S. I. A. Shah. "Trajectory optimisation for a rocket-assisted hypersonic boost-glide vehicle." Aeronautical Journal 121, no. 1238 (March 27, 2017): 469–87. http://dx.doi.org/10.1017/aer.2017.11.

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ABSTRACTIn this work, trajectory optimisation has been performed for a wing-body rocket assisted vehicle to compute the bestset of performance parameters including burn-out angle, angle-of-attack, bank-angle and throttle command that would result in optimal down-range and cross-range performance of the re-entry vehicle. An hp-adaptive Pseudospectral method has been used for the optimisation by combining the launch and rocket rocket-assisted re-entry stages. The purpose of the research is to compute optimal burn-out condition, angle-of-attack, bank-angle and optimal thrust segments that would maximise the down-range and cross-range performance of the hypersonic boost glide vehicle, under constrained heat rate environments. The variation of down-range/cross-range performance of rocket rocket-assisted hypersonic boost glide vehicle with bounds on diminishing heat rate has also been computed.

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36

Huang, Z. C., Y. S. Zhang, and Yao Liu. "Research on State Estimation of Hypersonic Glide Vehicle." Journal of Physics: Conference Series 1060 (July 2018): 012088. http://dx.doi.org/10.1088/1742-6596/1060/1/012088.

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37

Chen, Jian, Nannan Du, and Yu Han. "Decoupling Attitude Control of a Hypersonic Glide Vehicle Based on a Nonlinear Extended State Observer." International Journal of Aerospace Engineering 2020 (February 7, 2020): 1–11. http://dx.doi.org/10.1155/2020/4905698.

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Aiming at solving the attitude control problem of a hypersonic glide vehicle, this paper proposes a decoupling control method based on a nonlinear extended state observer (NESO). According to the decentralized robust control theory of Tornambè, the coupling terms and the uncertainties are regarded as generalized uncertainties, and the NESO-based estimation and compensation signals are added to the closed-loop control law. The theoretical deduction proves that the proposed method can ensure that the tracking error of the closed-loop system is uniformly bounded. The simulation is carried out on the hypersonic glide vehicle model and compared with the traditional subchannel feedback control method. The simulation results show that the designed decoupling control method has superior control performances, and the influence of channel-coupling and uncertainty is compensated to a great extent.

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38

Li, Zhengnan, Tao Yang, and Zhiwei Feng. "The Multiobjective Trajectory Optimization for Hypersonic Glide Vehicle Based on Normal Boundary Intersection Method." Mathematical Problems in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/9407238.

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To solve the multiobjective optimization problem on hypersonic glider vehicle trajectory design subjected to complex constraints, this paper proposes a multiobjective trajectory optimization method that combines the boundary intersection method and pseudospectral method. The multiobjective trajectory optimization problem (MTOP) is established based on the analysis of the feature of hypersonic glider vehicle trajectory. The MTOP is translated into a set of general optimization subproblems by using the boundary intersection method and pseudospectral method. The subproblems are solved by nonlinear programming algorithm. In this method, the solution that has been solved is employed as the initial guess for the next subproblem so that the time consumption of the entire multiobjective trajectory optimization problem shortens. The maximal range and minimal peak heat problem is solved by the proposed method. The numerical results demonstrate that the proposed method can obtain the Pareto front of the optimal trajectory, which can provide the reference for the trajectory design of hypersonic glider vehicle.

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Qiao, Qing Qing, and Wan Chun Chen. "Dynamic Inversion Guidance Law for a Hypersonic Vehicle." Advanced Materials Research 383-390 (November 2011): 4451–56. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.4451.

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An adapting dynamic inversion guidance law developed by using integral of time multiply by absolute error (ITAE) performance index for a hypersonic vehicle was studied. As a nominal trajectory, Maximum-Range glide trajectory was obtained by using collocation and successive quadratic programming. Dynamic inversion technique was employed to produce a guidance law which contains two PID controllers. To find optimal guidance parameters, ITAE criteria were used to tune the PID parameters. The numerical result showed that the guidance law was simple and efficient for a hypersonic vehicle flies along the optimal trajectory.

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Zhou, Huan, Wei Zheng, and Guojian Tang. "Ballistic error propagation algorithm for glide trajectory based on perturbation theory." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 9 (July 7, 2016): 1574–92. http://dx.doi.org/10.1177/0954410016656874.

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A ballistic error propagation algorithm for glide trajectories of a hypersonic glide vehicle is originally proposed based on the perturbation theory. Perturbation equations that treat perturbations as external inputs and flight state deviations as state variables are established. Based on the reasonable simplification assumptions, the analytic expression of the state transition matrix is deduced and thus the ballistic error propagation model is established. A transposed coordinate frame is introduced to simplify the development of the perturbation equations and the error propagation model. By employing the gravity anomaly as the single perturbation factor, the proposed algorithm is validated and verified by numerical experiments. When compared with the traditional method, the proposed method takes only just a quarter computational costs and restrains the method errors beneath 10% of the total terminal deviations. It is an effort that initially focuses on the error propagation mechanism of the glide trajectory and the proposed model has sufficient precision for the analysis of modeling deviations, thus laying the foundation of correcting the modeling deviations and enhancing the accuracy of vehicle’s flight states.

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41

Kumar, G. Naresh, D. Penchalaiah, A. K. Sarkar, and S. E. Talole. "Hypersonic Boost Glide Vehicle Trajectory Optimization Using Genetic Algorithm." IFAC-PapersOnLine 51, no. 1 (2018): 118–23. http://dx.doi.org/10.1016/j.ifacol.2018.05.020.

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42

Dong, Chunyun, Zhi Guo, and Xiaolong Chen. "Robust Trajectory Planning for Hypersonic Glide Vehicle with Parametric Uncertainties." Mathematical Problems in Engineering 2021 (January 16, 2021): 1–19. http://dx.doi.org/10.1155/2021/3676810.

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A hybrid double-loop optimization algorithm combing particle swarm optimization (PSO) and nonintrusive polynomial chaos (NIPC) is proposed for solving the robust trajectory optimization of hypersonic glide vehicle (HGV) under uncertainties. In the outer loop, the PSO method searches globally for the robust optimal control law according to a penalized fitness function that contains the system robustness considerations. In the inner loop, uncertainty propagation of the stochastic system is performed using the NIPC method, to provide statistical moments for the iterative scheme of the PSO method in the outer loop. Only control variables are discretized, and the state constraints are satisfied implicitly through the numerical integration process, which reduces the number of decision variables as well as the huge amount of computation increased by NIPC. In the end, the robust optimal control law is achieved conveniently. Numerical simulations are carried out considering a classical time-optimal trajectory optimization problem of HGV with uncertainties in both initial states and aerodynamic coefficients. The results demonstrate the feasibility and effectiveness of the proposed method.

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43

Hwang, Ki-Young, and Hwanil Huh. "Research and Development Trends of a Hypersonic Glide Vehicle (HGV)." Journal of the Korean Society for Aeronautical & Space Sciences 48, no. 9 (September 30, 2020): 731–43. http://dx.doi.org/10.5139/jksas.2020.48.9.731.

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Kumar, G. Naresh, AK Sarkar, and SE Talole. "Dynamic pressure based mid-course guidance scheme for hypersonic boost-glide vehicle." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 9 (August 24, 2018): 3211–22. http://dx.doi.org/10.1177/0954410018795265.

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In this study, a guidance scheme for an aerodynamically controlled hypersonic boost-glide class of flight vehicle is proposed. In this work, optimum glide dynamic pressure corresponding to maximum L/ D throughout the flight is calculated and a mid-course guidance law formulation to track the dynamic pressure while suppressing phugoid oscillations is proposed for real-time flight trajectory shaping. Efficacy of the proposed guidance scheme has been demonstrated through simulation studies. Robustness analysis on the proposed guidance algorithm is carried out using Monte Carlo technique. Lastly, a pattern search algorithm-based offline generated maximum L/ D optimal trajectory existing in literature, which meets minimum dynamic pressure, maximum airframe skin temperature, as well as other in-flight and terminal constraints is used as reference trajectory to evaluate the performance of the proposed guidance scheme.

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Yu, Shutian, Xinyue Ni, Xiaoyan Li, Tingliang Hu, and Fansheng Chen. "Real-time dynamic optimized band detection method for hypersonic glide vehicle." Infrared Physics & Technology 121 (March 2022): 104020. http://dx.doi.org/10.1016/j.infrared.2022.104020.

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Dong, Chunyun, and Yuanli Cai. "Reentry Trajectory Optimization for Hypersonic Glide Vehicle with Flexible Initial Conditions." Journal of Aerospace Engineering 30, no. 5 (September 2017): 04017033. http://dx.doi.org/10.1061/(asce)as.1943-5525.0000727.

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Jiang, Liang, Ying Nan, Yu Zhang, and Zhihan Li. "Anti-Interception Guidance for Hypersonic Glide Vehicle: A Deep Reinforcement Learning Approach." Aerospace 9, no. 8 (August 4, 2022): 424. http://dx.doi.org/10.3390/aerospace9080424.

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Anti-interception guidance can enhance a hypersonic glide vehicle (HGV) compard to multiple interceptors. In general, anti-interception guidance for aircraft can be divided into procedural guidance, fly-around guidance and active evading guidance. However, these guidance methods cannot be applied to an HGV’s unknown real-time process due to limited intelligence information or on-board computing abilities. In this paper, an anti-interception guidance approach based on deep reinforcement learning (DRL) is proposed. First, the penetration process is conceptualized as a generalized three-body adversarial optimal (GTAO) problem. The problem is then modelled as a Markov decision process (MDP), and a DRL scheme consisting of an actor-critic architecture is designed to solve this. Reusing the same sample batch during training results in fewer serious estimation errors in the critic network (CN), which provides better gradients to the immature actor network (AN). We propose a new mechanismcalled repetitive batch training (RBT). In addition, the training data and test results confirm that the RBT can improve the traditional DDPG-based-methodes.

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Xie, Yangfan, Xuebin Zhuang, Zepu Xi, and Hongbo Chen. "Dual-Channel and Bidirectional Neural Network for Hypersonic Glide Vehicle Trajectory Prediction." IEEE Access 9 (2021): 92913–24. http://dx.doi.org/10.1109/access.2021.3092515.

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Chen, Kai, Cheng-zhi Zeng, Sen-sen Pei, and Wen-chao Liang. "Normal gravity model for inertial navigation of a hypersonic boost-glide vehicle." Journal of Zhejiang University-SCIENCE A 23, no. 1 (January 2022): 55–67. http://dx.doi.org/10.1631/jzus.a2100133.

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Li, Hesong, Yi Wang, Yunfan Zhou, Shangcheng Xu, and Dan Su. "A Two-Level Optimization Method for Hypersonic Periodic Cruise Trajectory." International Journal of Aerospace Engineering 2021 (June 30, 2021): 1–11. http://dx.doi.org/10.1155/2021/9975007.

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Periodic cruise has the potential to improve the fuel-saving efficiency of hypersonic cruise vehicle but is difficult to optimize. In this paper, a two-level optimization method for the trajectory of periodic cruise is proposed. Due to that the periodic cruise trajectory can be divided into an acceleration phase where engine works and a glide phase where engine is off, the two-level optimization method is proposed to optimize the trajectory in each phase by the corresponding level. In the first level, Downhill Simplex Method (DSM) is employed to find an optimal angle of attack in the acceleration phase. Subsequently, the optimal trajectory in glide phase is obtained by the Pseudo-Spectral Method (PSM) in the second optimization level. Numerical results demonstrate the effectiveness of the proposed method. Finally, through comparing with steady-state cruise, it is concluded that periodic cruise makes full use of the change of atmospheric density and lift-drag ratio; thus, fuel saving is achieved.

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