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系统工程与电子技术（英文版）
系统工程与电子技术（英文版）

施荣

双月刊

1004-4132

tougaoxinxiang@263.net

010-68388406

100854

北京142信箱32分箱

系统工程与电子技术（英文版）/Journal Journal of Systems Engineering and ElectronicsCSCDCSTPCD北大核心EISCI
查看更多>>本刊是《中国科学引文数据库》来源期刊，被美国科学引文索引（SCIE）、美国工程索引（EI）和英国科学文摘（SA）等多家国内、外著名检索系统收录。它是面向高科技开发和应用的跨学科期刊，以传播新技术、促进学术交流为宗旨，坚持深度与广度、理论与应用相结合的方针，努力反映系统工程与电子技术两大领域的最新成就，报道的主要内容包括：系统科学、军事系统分析、飞行器控制、雷达、光电探测技术、信息获取与处理、运筹学管理与决策技术等。
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    Improved spatio-temporal alignment measurement method for hull deformation

    XU DongshengYU YuanjinZHANG XiaoliPENG Xiafu...
    485-494页
    查看更多>>摘要：In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial match-ing measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of iner-tial measurement unit modeling to establish a brand-new spatio-temporal aligned hull deformation measurement model.In addi-tion,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deforma-tion angle by the time-space alignment method of hull deforma-tion.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network

    YANG LuyiLI HaiyangZHANG JinZHU Yuehe...
    495-508页
    查看更多>>摘要：It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft.In this paper,the RD of free return orbits is quickly evaluated and calculated via the clas-sification and regression neural networks.An efficient database-generation method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit's inclination and right ascension of ascending node(RAAN)at the perilune.A classify neural network and a regression network are trained respectively.The former is built for classifying the type of the RD,and the latter is built for calculating the inclination and RAAN of the RD.The simulation results show that two neural networks are well trained.The classification model has an accu-racy of more than 99%and the mean square error of the regres-sion model is less than 0.01° on the test set.Moreover,a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached.The proposed deep learning method shows the superio-rity in computation efficiency compared with the traditional dou-ble two-body model.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    INSTRUCTIONS FOR AUTHORS

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      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普