火箭军工程大学 导弹工程学院,陕西 西安 710025
通信作者邮箱:xhf2phd@163.com
收稿:2025-05-14,
网络首发:2025-12-25,
纸质出版:2026-03
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袁梁弼, 徐慧, 蔡光斌, 等. 基于改进徒步优化算法的可达域插值计算[J]. 兵工学报, 2026,47(3):250369.
YUAN Liangbi, XU Hui, CAI Guangbin, et al. Interpolation Calculation for Reentry Reachable Domain Based on Improved Hiking Optimization Algorithm[J]. Acta Armamentarii, 2026, 47(3): 250369.
袁梁弼, 徐慧, 蔡光斌, 等. 基于改进徒步优化算法的可达域插值计算[J]. 兵工学报, 2026,47(3):250369. DOI: 10.12382/bgxb.2025.0369.
YUAN Liangbi, XU Hui, CAI Guangbin, et al. Interpolation Calculation for Reentry Reachable Domain Based on Improved Hiking Optimization Algorithm[J]. Acta Armamentarii, 2026, 47(3): 250369. DOI: 10.12382/bgxb.2025.0369.
高超声速滑翔飞行器作为空天突防关键力量,具有广泛应用前景。然而,该飞行器可达域计算仍面临复杂程度高、求解效率慢等问题。基于此,提出一种结合改进徒步优化算法与分段三次Hermite插值的再入可达域快速计算方法。通过累加Logistic-Sine正弦混沌映射与徒步更新-透镜反向学习迭代机制,提升徒步优化算法收敛性能。在此基础上建立动态速度节点,采用分段三次Hermite插值拟合离散落点,实现可达域边界快速计算。仿真结果表明:改进后的徒步优化算法收敛效率提升明显;分段三次Hermite插值拟合可达域具备较高精度,相较于椭圆边界、线性插值等方法,计算用时分别减少11.7%、54.1%。
Hypersonic glide vehicles(HGVs)
as a key force in aerospace defense
has broad application prospects nowadays. The computation of reentry reachable domain of HGVs
however
still faces problems such as high complexity and slow solution efficiency in group intelligent optimization algorithm. To fill this gap
this paper proposes a fast reentry reachable domain computation method combining the improved hiking optimization algorithm and piecewise cubic Hermite interpolating polynomial method. The convergence performance of the hiking optimization algorithm is improved by accumulating Logistic-Sine sinusoidal chaotic mapping and hiking update-lens reverse learning iteration mechanism. Based on the algorithm
a dynamic velocity node is established
and the piecewise cubic Hermite interpolating polynomial method is used to fit the discrete drop points
thereby enabling the rapid computation of reachable domain boundary. Simulated results show that the convergence efficiency of the improved hiking optimization algorithm is strengthened. Compared with the elliptic boundary and linear interpolation methods
the piecewise cubic Hermite interpolating polynomial method reduces the required computing time by 11.7% and 54.1%
respectively
with higher computational accuracy of reachable domain.
罗雨雨,丁伟,明振军,等.面向OODA作战流程的防空火力网端对端智能构建算法[J].兵工学报,2024,45(12):4231-4245.
LUO Y Y, DING W, MING Z J, et al. OODA combat process-oriented end-to-end intelligent construction algorithm for air defense fire network[J]. Acta Armamentarii, 2024, 45 (12):4231-4245. (in Chinese)
穆凌霞,王新民,谢蓉,等.高超音速飞行器及其制导控制技术综述[J].哈尔滨工业大学学报,2019,51(3):1-14.
MU L X, WANG X M, XIE R, et al. A review of hypersonic vehicles and their guidance and control technologies[J]. Journal of Harbin Institute of Technology,2019,51(3):1-14. (in Chinese)
冯振欣,张恒毅,郭建国.空间飞行器可达域求解研究进展与展望[J].空天技术,2024 (5):14-32.
FENG Z X, ZHANG H Y, GUO J G. Research progress and prospects on reachability analysis and solution methods for spacecraft[J].Advances in Aerospace Technology,2024(5):14-32. (in Chinese)
徐慧,蔡光斌,崔亚龙,等.高超声速滑翔飞行器再入轨迹优化[J].哈尔滨工业大学学报,2023,55(4):44-55.
XU H,CAI G B,CUI Y L,et al. Reentry trajectory optimization of hypersonic glide vehicles[J]. Journal of Harbin Institute of Technology,2023,55(4):44-55. (in Chinese)
王铮,邢晓露,闫天,等.高超声速飞行器突防制导的发展现状与未来发展方向[J].飞航导弹,2021(7):18-24,67.
WANG Z,XING X L,YAN T,et al. Development status and future directions of penetration guidance for hypersonic vehicles[J]. Aerodynamic Missile Journal,2021(7):18-24,67. (in Chinese)
胡雨传,代京,易娟,等.基于神经网络的再入飞行器可达域生成方法[J].计算机仿真,2024,41(5):12-17.
HU Y C, DAI J, YI J, et al. Neural network-based generation method for reachable domain of reentry vehicle[J]. Computer Simulation,2024,41(5):12-17. (in Chinese)
余跃,王宏伦.基于深度学习的高超声速飞行器再入预测校正容错制导[J].兵工学报,2020,41(4):656-669.
YU Y,WANG H L. Deep learning-based reentry predictor-corrector fault-tolerant guidance for hypersonic vehicles[J]. Acta Armamentarii,2020,41(4):656-669. (in Chinese)
吴楠,王锋,赵敏,等.高超声速滑翔再入飞行器的可达区快速预测[J].国防科技大学学报,2021,43(1):1-6.
WU N,WANG F,ZHAO M,et al. Fast prediction for footprint of hypersonic glide reentry vehicle[J]. Journal of National University of Defense Technology,2021,43(1):1-6. (in Chinese)
冉云霆,泮斌峰.多约束下升力式再入飞行器可达域计算方法[J].北京航空航天大学学报,2025,51(3):904-909.
RAN Y T,PAN B F. Computation method for reachable domain of lift reentry vehicle under multiple constraints[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(3):904-909. (in Chinese)
章吉力,刘凯,樊雅卓,等.考虑禁飞区规避的空天飞行器分段预测校正再入制导方法[J].宇航学报,2021,42(1):122-131.
ZHANG J L, LIU K, FAN Y Z, et al. Segmented predictor-corrector reentry guidance method for aerospace vehicles considering no-fly zone avoidance[J]. Journal of Astronautics, 2021,42(1):122-131. (in Chinese)
李兆亭,周祥,张洪波,等.一种近似解析的再入滑翔飞行器可达域快速生成方法[J].航天控制,2023,41(4):27-33.
LI Z T,ZHOU X,ZHANG H B,et al. An approximate analytical fast generation method for reachable domain of reentry glide vehicle[J]. Aerospace Control, 2023, 41 (4): 27- 33. (in Chinese)
李兆亭,周祥,张洪波,等.基于伪谱法的再入可达域影响因素分析[J].上海交通大学学报,2022,56(11):1470-1478.
LI Z T, ZHOU X, ZHANG H B, et al. Analysis of influencing factors for reentry reachable domain based on pseudospectral method[J]. Journal of Shanghai Jiao Tong University,2022, 56(11):1470-1478. (in Chinese)
张晚晴,余文斌,李静琳,等.基于纵程解析解的飞行器智能横程机动再入协同制导[J].兵工学报,2021,42(7):1400-1411.
ZHANG W Q, YU W B, LI J L, et al. Cooperative reentry guidance for intelligent lateral maneuver of hypersonic vehicle based on longitudinal analytical solution[J]. Acta Armamentarii, 2021,42(7):1400-1411. (in Chinese)
蔺君,何英姿,黄盘兴.基于差分进化算法的再入可达域快速计算[J].中国空间科学技术,2020,40(4):54-60.
LIN J, HE Y Z, HUANG P X. Fast computation of reentry reachable domain based on differential evolution algorithm[J]. Chinese Space Science and Technology,2020,40(4):54-60. (in Chinese)
赵江,周锐.基于粒子群优化的再入可达区计算方法研究[J].兵工学报,2015,36(9):1680-1687.
ZHAO J,ZHOU R. Research on computation method for reentry reachable domain based on particle swarm optimization[J]. Acta Armamentarii,2015,36(9):1680-1687. (in Chinese)
梁巨平,周韬,周浩.再入飞行器平稳滑翔可达区域计算分析[J].兵器装备工程学报,2018,39(5):112-116.
LIANG J P, ZHOU T, ZHOU H. Computation and analysis of reachable domain for reentry vehicle in steady glide[J]. Journal of Ordnance Equipment Engineering,2018,39(5):112-116. (in Chinese)
ABBEL-SALAM M, ALOMARI S A, ALMOMANI M H, et al. Quadruple strategy-driven hiking optimization algorithm for low and high-dimensional feature selection and real-world skin cancer classification[J]. Knowledge-Based Systems,2025,315:113286.
周宏宇,王小刚,单永志,等.基于改进粒子群算法的飞行器协同轨迹规划[J].自动化学报,2022,48(11):2670-2676.
ZHOU H Y,WANG X G,SHAN Y Z,et al. Cooperative trajectory planning for vehicles based on improved particle swarm optimization algorithm[J]. Acta Automatica Sinica, 2022,48(11):2670-2676. (in Chinese)
徐慧,蔡光斌,张胜修.高超声速滑翔飞行器再入气动系数改进拟合模型[J].宇航学报,2021,42 (9):1139-1149.
XU H, CAI G B, ZHANG S X. Modified aerodynamic coefficient fitting models for hypersonic glide vehicle during reentry phase[J]. Journal of Astronautics,2021,42(9):1139-1149. (in Chinese)
傅瑜,杨卫丽,崔乃刚.升力式再入飞行器覆盖范围计算分析[J].哈尔滨工业大学学报,2012,44 (11):13-19.
FU Y, YANG W L, CUI N G. Computation and analysis of coverage area for lift reentry vehicle[J]. Journal of Harbin Institute of Technology,2012,44(11):13-19. (in Chinese)
李忠洪,王蕊,王洁,等.累加正弦化混沌系统模型的性能分析[J].重庆师范大学学报(自然科学版),2024,41(5):95-105.
LI Z H, WANG R, WANG J, et al. Performance analysis of additive sinusoidal chaotic system model[J].Journal of Chongqing Normal University(Natural Science),2024,41(5):95-105. (in Chinese)
OLADEJO S O, EKWE S O, MIRJALILI S. The hiking optimization algorithm: a novel human-based metaheuristic approach[J]. Knowledge-Based Systems,2024,296:111880.
顾清华,姜秉佼,常朝朝,等.求解大规模优化问题的改进麻雀搜索算法[J].控制与决策,2023,38(7):1960-1968.
GU Q H,JIANG B J,CHANG C C,et al. Improved sparrow search algorithm for solving large-scale optimization problems[J]. Control and Decision,2023,38(7):1960-1968. (in Chinese)
RABBATH C A, CORRIVEAU D. A comparison of piecewise cubic Hermite interpolating polynomials, cubic splines and piecewise linear functions for the approximation of projectile aerodynamics[J]. Defence Technology,2019,15(5):741-757.
张伟,高正红,王超,等.无参数自适应罚函数的高效代理模型优化设计方法[J].北京航空航天大学学报,2024,50(4):1262-1272.
ZHANG W,GAO Z H,WANG C,et al. Efficient surrogate model optimization design method with parameter-free adaptive penalty function[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(4):1262-1272. (in Chinese)
周宏宇,王小刚,赵亚丽,等.空天飞行器返回滑翔段在线制导方法[J].宇航学报,2021,42 (2):175-184.
ZHOU H Y,WANG X G,ZHAO Y L,et al. Online guidance for aerospace vehicle in return-gliding phase[J]. Journal of Astronautics,2021,42(2):175-184. (in Chinese)
李宪强,马戎,张伸,等.蚁群算法的改进设计及在航迹规划中的应用[J].航空学报,2020,41(增刊2):213-219.
LI X Q,MA R,ZHANG S,et al. Improved design of ant colony algorithm and its application in path planning[J]. Acta Aeronautica et Astronautica Sinica,2020,41(S2):213-219. (in Chinese)
徐明,王风富,龙文.多策略改进的徒步优化算法及其应用[J].电子测量技术,2025,48(3):60-73.
XU M, WANG F F, LONG W. Multi-strategy improved hiking optimization algorithm and its application[J].Electronic Measurement Technology,2025,48(3):60-73. (in Chinese)
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