Obtaining good measurement performance with meter wave radar has always been a difficult problem. Especially in low-elevation areas, the multipath effect seriously affects the measurement accuracy of meter wave radar. The generalized multiple signal classification (MUSIC) algorithm is a well-known measurement method that dose not require decorrelation processing. The polarization-sensitive array (PSA) has the advantage of polarization diversity, and the polarization smoothing generalized MUSIC algorithm demonstrates good angle estimation performance in low-elevation areas when based on a PSA. Nevertheless, its computational complexity is still high, and the estimation accuracy and discrimination success probability need to be further improved. In addition, it cannot estimate the polarization parameters. To solve these problems, a polarization synthesis steering vector MUSIC algorithm is proposed in this paper. First, the MUSIC algorithm is used to obtain the spatial spectrum of the meter wave PSA. Second, the received data are properly deformed and classified. The Rayleigh–Ritz method is used to decompose the angle to realize the decoupling of polarization and the direction of the arrival angle. Third, the geometric relationship and prior information of the direct wave and the reflected wave are used to continue dimension reduction processing to reduce the computational complexity of the algorithm. Finally, the geometric relationship is used to obtain the target height measurement results. Extensive simulation results illustrate the accuracy and superiority of the proposed algorithm.
在基于合成孔径雷达(SAR)图像的舰船目标检测中,针对图像背景复杂、舰船尺寸大小不一等问题,提出了一种改进的YOLOv3深度卷积神经网络(CNN),用于SAR图像中的舰船目标检测.该方法基于训练数据集中的尺寸标签信息,使用交并比作为距离度量,利用k-means聚类方法为舰船目标提取了九组先验锚点框作为后续候选框边框参数优化的初始值;引入rGIOU来代替交并比rIOU,用于更新框回归损失和置信度损失,从而得到更加合理的损失函数,能将候选框与标注框之间的相对位置信息引入候选框的边框参数优化.为了验证改进版YOLOv3网络的性能,文中基于高分辨SAR舰船检测数据集AIR-SARShip-2.0,利用平移、翻转、调整亮度等方法进行数据集扩充,得到训练数据集和测试数据集,并进行舰船目标检测实验.实验结果表明:相较于常规YOLOv3网络和Faster R-CNN网络,改进YOLOv3网络在舰船目标检测上的总体效果更好,具有更高的准确率和更少的虚警,提高了平均精度指标,且需要的计算时间更少.
复杂电磁环境下,雷达、通信等信号在时域、频域、时频域存在复杂混叠,且各类型信号带宽差异大、调制样式多样,常规信号分离方法难以应用.文中提出了一种基于信号重构的非参数化混叠信号分离方法.基于瞬时幅度的傅里叶分解,建立非参数化稀疏信号模型,将混叠信号分离转化为瞬时幅度和瞬时频率的联合估计问题,基于交替迭代思路,分别进行估计和更新.对于瞬时幅度项,基于广义近似消息传递方法进行估计;对于瞬时频率项,利用瞬时频率变化平缓性特征,建立瞬时频率更新模型,实现对瞬时频率的更新.进一步,基于瞬时幅度和瞬时频率估计结果进行各信号重构,实现混叠信号分离.仿真结果表明:文中所提方法能有效分离时频域复杂混叠信号.
针对机载火控雷达空空工作模式识别局限性大的问题,从电子情报和雷达告警系统的视角定义了八种工作状态,提出了基于一维卷积神经网络的识别方法.基于不同工作状态的波形特征开发了信号模拟器,构建了全脉冲数据预处理和工作状态自动识别的一维卷积神经网络结构,迭代训练确定最优的网络参数完成状态识别.仿真结果表明:文中提出的识别方法精度高,且对信噪比小、错漏脉冲多的信号适应能力强,具有较强的工程应用价值.
提出了一种基于空频域波形设计的雷达通信共享系统,即对多输入多输出发射波形在空域和频域进行优化,利用优化的发射方向图主瓣实现对目标区域的雷达探测,通过控制通信方位的发射方向图旁瓣水平以及通信频带上的功率谱密度水平来实现通信信息传输.为此,在方向图旁瓣电平、波形功率谱水平、波形恒模等约束下,以发射方向图的匹配误差为目标函数,建立了相应的波形优化问题,并采用半正定松弛方法和高斯随机化方法来求解该问题.文中给出了通信信息的解调过程,且分别验证了雷达性能和通信性能.
为应对以民用无人机为代表的低小慢目标"黑飞""滥飞"所带来的低空安全威胁以及巡航导弹、战术导弹所带来的低空军事威胁,文中引入数字波束合成技术,设计并实现了一种面向低空预警雷达的信号处理控制平台,该平台具有实时性强、运算量大、传输速率高等特点.通过选用高速光纤传输与串行总线VPX技术,同时采用高性能模数转换器、超大规模现场可编程门阵列及高速专用数字信号处理芯片,实现了此平台的硬件架构设计,并在此平台上实现了一种基于数据流驱动的软件信号处理方案.得益于灵活的系统架构和丰富的硬件资源,该信号处理控制平台可以适应新技术的快速应用,便于低空预警雷达功能的升级扩展及性能的进一步提升,有效应对低空威胁.
天波超视距雷达工作在时变的电离层传输状态下,通过回波能量难以对空中目标的雷达散射截面积(RCS)进行有效估计.为此,提出了一种基于海杂波修正的目标RCS估计方法,建立了 RCS估计卡尔曼滤波模型和RCS仿真数据辅助模型.通过两型民航目标的仿真和实测数据验证了所提模型的有效性,其在不同时段、雷达工作状态和电离层传输条件下,实现了对目标RCS和电离层损耗的稳健估计,并利用目标电磁仿真数据进一步辅助提高了对已知类型目标的估计效率和准确性.
Optoelectronic oscillator（OEO） is a novel promising high quality microwave signal generator. The OEO′s high frequency, multi-mode oscillation character requires that there must be a narrow band filter in the loop. The method of reducing phase noise by increasing the fiber length is limited by the filter′s relative bandwidth. An assistant frequency conversion technology is innovated. It can be broaden the filter′s relative bandwidth by lowering the filtering frequency, and cancel the local oscillator′s phase noise at the same time. The OEO with this technology can break through the fiber length limit theoretically, and has lower phase noise. Experiments are done to compare the phase noise of OEOs with and without the technology. It is clear that the OEO with this technology can use the longer fiber and reduce the phase noise significantly.
Leap Motion is widely used in various virtual installations due to its high tracking accuracy and good gesture interaction. The Leap Motion gesture recognition is applied to high-precision virtual installation of highly integrated large-scale structural parts, which can realize the interactive control of the installation process by the virtual hand. A fuzzy k-nearest neighbor（KNN） classification method based on weighted chi-square distance is designed to achieve virtual gesture classification. Different weights are assigned according to the importance of gesture features, which can further improve the classification accuracy. The test results show that the improved classification method has a recognition accuracy of 92.7%. It is 5.3% higher than traditional classification algorithms. Three kinds of gestures are used for virtual installation experiments of engine components. The results show that gesture recognition has achieved good results in the installation process, which can improve the quality and efficiency of the actual installation process, and it is of great significance to improve the manufacturing and installation level of large military products.
针对电子对抗领域难以对机载相控阵火控雷达的工作模式进行有效判定的问题,提出了一种多特征联合的相控阵火控雷达工作模式判定方法.以长时间海量雷达侦察数据挖掘和情报资料分析为基础,从电子侦察角度分析了机载相控阵火控雷达的典型工作模式及其侦收波形特征,并结合工程实现设计了四种可用的模式判定特征维度;借鉴DS证据理论,提出了工作模式判定方法并进行算法仿真验证.仿真结果表明:该方法可以实现判定机载相控阵火控雷达不同工作模式的目的,满足电子对抗领域相关需求.
随着信息化时代的到来,数字化信息呈指数模式增长,并且在人们的生活与工作中扮演越来越重要的角色.根据全球权威部门Statista的统计和预测,2009年世界数字信息总量还不到1ZB,2020年的世界数字信息总量将超过第47ZB,而到2035年这个数字预计将来到2142ZB.
阐述了超短波超视距无源侦察系统的工作机理,分析了利用超视距辐射源信号形成视距或超视距目标定位的典型模式,探讨了定位系统工程实现的主要挑战和解决措施.文中推导了目标反射超视距辐射源能量的表达式,论述了辐射源特性和选用依据,并以无线电视和雷达为典型外辐射源分析了目标定位范围.仿真分析表明,利用超视距辐射源,可检测辐射源周边、辐射源与侦察系统视距交汇区域及周边的空中目标,从而有效扩展被动定位范围,形成超视距跟踪和预警能力.
Synthetic aperture radar（SAR） moving target detection is a key technology in radar signal processing. In this paper, a multi-channel SAR ground moving target detection algorithm based on convolutional neural network（CNN） is proposed by using deep learning high-dimensional feature extraction capability. Aiming at the problem that radar measured data is less and moving target samples are difficult to obtain, a network training method based on simulation-measured mixed sample set is proposed to complete the high-precision training of the network. The measured data detection results show that this method can effectively complete the ground moving target detection, has significant advantages compared with the traditional moving target detection method.
Aiming at the problem that the square root cubature Kalman filter Gaussian mixture probability hypothesis density（SRCKF-GM-PHD） algorithm is not strong in tracking non-linear targets under the condition of the high clutter, in this paper firstly the improved grey wolf optimizer is infused to adjust the process noise Q and measurement noise R in real time. Secondly, the gain matrix of SRCKF-GM-PHD algorithm is adjusted to enhance the tracking accuracy of the target with the idea of improved fading factors. In addition, in order to avoid discontinuing the algorithm, an improved measure of dynamic weight adjustment strategy is proposed to adjust the covariance of the actual output residual sequence in the algorithm. Finally, a novel SRCKF-GM-PHD algorithm combining the improved grey wolf optimizer and the improved fading factors is formed. The performances of the four algorithms are compared by simulation analysis, and the validity and superiority of the proposed algorithm in tracking accuracy are demonstrated.
常规空中目标轨迹识别方法能够识别单一轨迹样式,但对于复杂轨迹样式识别效果差.文中提出一种基于Softmax多分类网络的空中目标自适应分段轨迹识别算法.首先,通过滑窗在时间上遍历整条复杂轨迹序列,在窗内利用设计的拟合方程对窗内轨迹进行拟合,得到方程参数;然后,基于方程参数训练Softmax分类网络模型,完成基于方程参数的窗内轨迹样式识别;最后,考虑到窗内识别错误及其特征,将识别结果进行同类合并,并基于Haar小波重构对识别结果进行修正,消除离散错误识别结果.仿真结果表明:文中所提方法能有效地对复杂轨迹样式进行分段识别.
为了提高路面的强度和耐用性,一般会在路面下进行钢筋加固,钢筋回波与待检测的灾害目标回波在时空域上可能会产生严重的混叠.为了对灾害目标进行有效的检测与成像,文中提出一种钢筋回波干扰下的灾害目标成像方法.首先,利用快速双曲线曲波变换将雷达接收信号变换到多个不同的尺度空间,在该空间中所有目标的能量是聚集的且相互分离;然后,进行钢筋回波滤波,将灾害目标的回波数据重构到时空域后再变换到波数域,在该域下考虑多层地下介质中电磁波波速变化的特点;最后,再反变换到时空域进行灾害目标成像.文中所提成像方法均采用快速处理算法,提高了运算速度,且适用于多层地下介质中钢筋回波干扰下的灾害目标成像.仿真结果证明了本文所提算法的有效性.
随着信息化时代的到来,数字化信息呈指数模式增长,并且在人们的生活与工作种扮演越来越重要的角色.根据全球权威部门Statista的统计和预测,2009年世界数字信息总量还不到1ZB,2020年的世界数字信息总量将超过第47ZB,而到2035年这个数字预计将来到2142ZB.当前,数字化信息已经成为人们重要的生产资料和战略资源.信息的高价值伴随而来的就是信息安全等一系列问题,当下人们越来越关注网络信息安全问题.然而,现在的网络信息安全存在威胁更加隐蔽、专业化程度更高等特点,这就要求进一步强化以计算机网络技术为核心的网络信息安全防护体系,以实现信息的应用安全与可靠,真正促进信息效能的最大化.
Behavior parameter test of active jammer is the premise and foundation of radar anti-jamming technology, and has important research value. For the jammer behavioral level parameter testing problem of digital radio frequency memory（DRFM）, a behavior parameter test scheme for DRFM jammer based on sequential waveform is proposed in this paper. The scheme realizes the analysis and estimation of jammer channelization, frequency targeting, forwarding, sorting and strategy mode capability, which provides a new idea for effectively countering DRFM jammer. At the same time, the jamming ability recognition algorithm based on analytic hierarchy process（AHP） and technique for order preference by similarity to ideal solution（TOPSIS） is proposed. The simulation results show that the recognition accuracy of this scheme is more than 90% when the interference to noise ratio is 2 dB.
广播式自动相关监视器(ADS-B)是一种用于空中交通管制的监视设备,因为其优越的各项性能,在雷达监视领域被广泛推广.为了方便快捷地测试ADS-B设备的准确性、可靠性和及时性等技术指标,需要使用目标模拟器来生成各种场景的ADS-B射频测试信号,包括不同的衰减、时延、多普勒频移和交织情况等.文中给出了一种基于数字射频调制技术的目标模拟器设计与实现,阐明了其工作原理与具体实现方法.对该模拟器的测试和使用表明:该模拟器可按照设定产生多个ADS-B目标叠加信号,操作简单且运行稳定,能够实现对ADS-B接收系统性能和功能测试,具有很好的应用价值.
A miniaturization radio frequency(RF)interface design with low insertion loss and high port isolation is proposed in this paper.This RF interface works in X-band and adopts ball grid array(BGA)technology as interface of RF module system instead of traditional electrical connectors by transmitting the RF signal to the interface of RF module system through the transmission path and vertical transition embedded in substrate board.Feasibility analysis is introduced and critical parameters of this interface cir-cuit are calculated with high frequency simulation software.A specialized test fixture is also designed and manufactured to obtain the electrical performance of the interface design.The test result shows that in frequency range of 8 GHz to 12 GHz,voltage static wave ratio(VSWR)of this RF transfer structure can reach the level below 1.2,the insertion loss can reach the level better than 0.1 dB,and isolation between ports is less than-80 dB.An X-band T/R module is designed based on this interface technology and several samples are manufactured and measured which can satisfy the required electrical performance.
