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目标机动补偿的动能拦截器增量式制导方法

陈旸 方艺忠 韩拓 胡庆雷

陈旸,方艺忠,韩拓,等. 目标机动补偿的动能拦截器增量式制导方法[J]. 北京航空航天大学学报,2024,50(3):831-838 doi: 10.13700/j.bh.1001-5965.2022.0519
引用本文: 陈旸,方艺忠,韩拓,等. 目标机动补偿的动能拦截器增量式制导方法[J]. 北京航空航天大学学报,2024,50(3):831-838 doi: 10.13700/j.bh.1001-5965.2022.0519
CHEN Y,FANG Y Z,HAN T,et al. Incremental guidance method for kinetic kill vehicles with target maneuver compensation[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):831-838 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0519
Citation: CHEN Y,FANG Y Z,HAN T,et al. Incremental guidance method for kinetic kill vehicles with target maneuver compensation[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(3):831-838 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0519

目标机动补偿的动能拦截器增量式制导方法

doi: 10.13700/j.bh.1001-5965.2022.0519
基金项目: 国家自然科学基金(61960206011,62203031);北京市自然科学基金(JQ19017);浙江省自然科学基金(LD22E050004);博士后创新人才支持计划(BX20220370);中国博士后科学基金(2022M710312)
详细信息
    通讯作者:

    E-mail:hantuo@buaa.edu.cn

  • 中图分类号: V488.133

Incremental guidance method for kinetic kill vehicles with target maneuver compensation

Funds: National Natural Science Foundation of China (61960206011,62203031);Beijing Natural Science Foundation (JQ19017);Zhejiang Provincial Natural Science Foundation (LD22E050004);China National Postdoctoral Program for Innovative Talents (BX20220370);China Postdoctoral Science Foundation (2022M710312)
More Information
  • 摘要:

    面向目标强机动、推力干扰、测量偏差的动能拦截器强抗扰末制导方法设计问题,提出一种目标机动补偿的大气层外动能拦截器增量式强抗扰末制导方法。通过回采推力传感信息、视线转率辅助微分信息,同时联合增量式制导方法与惯性时延的扰动估计方法,对目标机动等不确定性和内外部不确定性等带来的扰动进行实时补偿并融合至制导算法,从而实现复杂工况下拦截器对抗机动目标的制导系统扰动降级与鲁棒增强等目的。复杂工况下仿真结果表明:所提方法对强机动目标、测量偏差、推力干扰等多源扰动具有强抗扰能力,并且能够实现精确碰撞式拦截任务。

     

  • 图 1  三维末制导几何场景

    Figure 1.  Three-dimensional terminal guidance geometric scene

    图 2  标称情况惯性系下三维拦截轨迹

    Figure 2.  Three-dimensional interception trajectories under nominal conditions

    图 3  标称情况下轨控推力

    Figure 3.  Orbit control thrusts under nominal conditions

    图 4  标称情况下姿控力矩

    Figure 4.  Attitude control moments under nominal conditions

    图 5  蒙特卡罗打靶脱靶量分布

    Figure 5.  Miss distance distribution under Monte Carlo test

    图 6  蒙特卡罗打靶燃料消耗分布

    Figure 6.  Fuel consumption distribution under Monte Carlo test

    图 7  不确定情况下高机动目标的三维拦截轨迹

    Figure 7.  Three-dimensional interception trajectories against highly maneuvering target with uncertainties

    图 8  不确定情况下高机动目标的轨控推力

    Figure 8.  Orbit control thrust against highly maneuvering target with uncertainties

    图 9  扰动估计特性

    Figure 9.  Disturbance estimation performance

    表  1  抗扰能力对比

    Table  1.   Comparison of anti-disturbance capability

    制导律 增益条件 系统扰动 收敛域
    $ {A_{{\textit{z}}{\rm{M}}}} = \dfrac{{{f_{\textit{z}}} + {k_{\textit{z}}}\alpha }}{{{b_{\textit{z}}}}} $ $ {k_{\textit{z}}} > \dfrac{{\left| {{d_{\textit{z}}}} \right|}}{{\left| \alpha \right|}} $ $ \left| {{d_{\textit{z}}}} \right| $ $ \left| \alpha \right| \leqslant \dfrac{{\left| {{d_{\textit{z}}}} \right|}}{{{k_{\textit{z}}}}} $
    $ \Delta {A_{{\textit{z}}{\rm{Mc}}}} = \dfrac{{{{\dot \alpha }_0} + {k_{{\textit{z}}{\rm{i}}}}\alpha + \Delta {{\hat d}_{\textit{z}}}}}{{{b_{{\textit{z}}0}}}} $ $ {k_{{\textit{z}}{\rm{i}}}} > \dfrac{{\left| {\Delta {{\tilde d}_{\textit{z}}}} \right|}}{{\left| \alpha \right|}} $ $ \left| {\Delta {{\tilde d}_{\textit{z}}}} \right| $ $ \left| \alpha \right| \leqslant \dfrac{{\left| {\Delta {{\tilde d}_{\textit{z}}}} \right|}}{{{k_{{\textit{z}}{\rm{i}}}}}} $
    下载: 导出CSV

    表  2  不同制导方法结果对比

    Table  2.   Comparison results of different guidance methods

    制导方法 仿真情形 脱靶量/m 燃料消耗/kg
    NDI 标称低机动 0.920 1.995
    偏差高机动 2.015 3.245
    INDI 标称低机动 0.394 1.930
    偏差高机动 0.405 3.157
    PN 标称低机动 0.870 1.971
    偏差高机动 2.553 3.655
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-06-21
  • 录用日期:  2022-09-27
  • 网络出版日期:  2022-10-09
  • 整期出版日期:  2024-03-27

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