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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。
正式出版
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    Disparity estimation for multi-scale multi-sensor fusion

    SUN GuoliangPEI ShanshanLONG QianZHENG Sifa...
    259-274页
    查看更多>>摘要：The perception module of advanced driver assis-tance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor com-posed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experi-ments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map esti-mation.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Fast measurement and prediction method for electromagnetic susceptibility of receiver

    CHEN YanLU ZhonghaoLIU Yunxia
    275-285页
    查看更多>>摘要：Aiming at evaluating and predicting rapidly and accu-rately a high sensitivity receiver's adaptability in complex elec-tromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone test.Firstly,two signal genera-tors are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the inter-mediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent analysis.Secondly,the IF output response data are modeled and analyzed to con-struct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the receiver.An experiment performed on a radar receiver confirms the relia-bility of the method proposed in this paper.It shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity model.Based on this,fast and comprehensive evaluation and prediction of the receiver's EMS in complex environment can be efficiently realized.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Efficient unequal error protection for online fountain codes

    SHI PengchengWANG ZhenyongLI DezhiLYU Haibo...
    286-293页
    查看更多>>摘要：In this paper,an efficient unequal error protection(UEP)scheme for online fountain codes is proposed.In the build-up phase,the traversing-selection strategy is proposed to select the most important symbols(MIS).Then,in the completion phase,the weighted-selection strategy is applied to provide low overhead.The performance of the proposed scheme is ana-lyzed and compared with the existing UEP online fountain scheme.Simulation results show that in terms of MIS and the least important symbols(LIS),when the bit error ratio is 10-4,the proposed scheme can achieve 85%and 31.58%overhead reduction,respectively.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Sound event localization and detection based on deep learning

    ZHAO DadaDING KaiQI XiaogangCHEN Yu...
    294-301页
    查看更多>>摘要：Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research fields.In recent years,in order to achieve a more complete spa-tial and temporal representation of sound field,sound event localization and detection(SELD)has become a very active research topic.This paper presents a deep learning-based multi-overlapping sound event localization and detection algorithm in three-dimensional space.Log-Mel spectrum and generalized cross-correlation spectrum are joined together in channel dimen-sion as input features.These features are classified and regressed in parallel after training by a neural network to obtain sound recognition and localization results respectively.The channel attention mechanism is also introduced in the network to selectively enhance the features containing essential informa-tion and suppress the useless features.Finally,a thourough comparison confirms the efficiency and effectiveness of the pro-posed SELD algorithm.Field experiments show that the pro-posed algorithm is robust to reverberation and environment and can achieve higher recognition and localization accuracy com-pared with the baseline method.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Localization for mixed near-field and far-field sources under impulsive noise

    GAO HongyuanZHANG YuzeDU Ya'nanCHENG Jianhua...
    302-315页
    查看更多>>摘要：In order to solve the problem that the performance of traditional localization methods for mixed near-field sources(NFSs)and far-field sources(FFSs)degrades under impulsive noise,a robust and novel localization method is proposed.After eliminating the impacts of impulsive noise by the weighted out-lier filter,the direction of arrivals(DOAs)of FFSs can be esti-mated by multiple signal classification(MUSIC)spectral peaks search.Based on the DOAs information of FFSs,the separation of mixed sources can be performed.Finally,the estimation of localizing parameters of NFSs can avoid two-dimension spectral peaks search by decomposing steering vectors.The Cramer-Rao bounds(CRB)for the unbiased estimations of DOA and range under impulsive noise have been drawn.Simulation expe-riments verify that the proposed method has advantages in pro-bability of successful estimation(PSE)and root mean square error(RMSE)compared with existing localization methods.It can be concluded that the proposed method is effective and reliable in the environment with low generalized signal to noise ratio(GSNR),few snapshots,and strong impulse.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

    WEI ShaopengZHANG LeiLU JingyueLIU Hongwei...
    316-329页
    查看更多>>摘要：In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is fol-lowed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    An angular blinking jamming method based on electronically controlled corner reflectors

    GAN LinWU ZehaoWANG XuesongLI Jianbing...
    330-338页
    查看更多>>摘要：Passive jamming is believed to have very good poten-tial in countermeasure community.In this paper,a passive angu-lar blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitude of the incident wave can be modulated by switching the corner reflector between the penetration state and the reflection state,and the ensemble of multiple corner reflectors with towing rope can result in complex angle decoying effects.Dependency of the decoying effect on corner reflectors'radar cross section and positions are analyzed and simulated.Results show that the angle measured by a monopulse radar can be significantly interfered by this method while the automatic tracking is employed.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Coarse-fine joint target parameter estimation method based on AN-RSC in OFDM passive radar

    WANG ChujunWAN XianrongYI JianxinCHENG Feng...
    339-349页
    查看更多>>摘要：In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogo-nal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estima-tion accuracy of target parameters without excessive computa-tional burden.Firstly,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of tar-gets.Then,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler domain.At the same time,a reference signal compensation(RSC)method is presented to obtain high-precision delay estimation.Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of tar-get parameters compared with other algorithms.In addition,the proposed method also possesses computational advantages compared with the joint parameter estimation.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    A target parameter estimation method via atom-reconstruction in radar mainlobe jamming

    ZHOU BileiLIU WeijianLI RongfengCHEN Hui...
    350-360页
    查看更多>>摘要：Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppres-sion of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can sup-press the MLJ and simultaneously provide high estimation accu-racy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and pla-nar array.Moreover,the proposed method can effectively esti-mate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普

    Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

    CHEN ChenQUAN WeiSHAO Zhuang
    361-373页
    查看更多>>摘要：Aerial threat assessment is a crucial link in modern air combat,whose result counts a great deal for commanders to make decisions.With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data,a threat assessment method based on self-attention mechanism and gated recurrent unit(SA-GRU)is proposed.Firstly,a threat feature system including air combat situations and capability features is established.More-over,a data augmentation process based on fractional Fourier transform(FRFT)is applied to extract more valuable information from time series situation features.Furthermore,aiming to cap-ture key characteristics of battlefield evolution,a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently,after the concatenation of the processed air com-bat situation and capability features,the target threat level will be predicted by fully connected neural layers and the softmax classifier.Finally,in order to validate this model,an air combat dataset generated by a combat simulation system is introduced for model training and testing.The comparison experiments show the proposed model has structural rationality and can per-form threat assessment faster and more accurately than the other existing models based on deep learning.
      原文链接:
    • NETL
    • NSTL
    • 万方数据
    • 维普