基于周期样本图重构的雷达PRI调制类型识别算法研究

为提升对雷达脉冲重复间隔(pulse repetition interval, PRI)的分析性能,提出了一种基于周期样本图重构的雷达PRI调制类型识别算法。首先,建立了雷达PRI调制模型,分析了不同调制类型的信号特点;其次,利用到达时间(time of arrival, TOA)多阶差分序列估计了雷达PRI调制周期,并基于直方图算法重构了PRI周期样本图;然后,以PRI周期样本图为基础,提出了5个PRI调制特征实现PRI调制类型识别;该方法不仅能够提升PRI调制类型的识别准确率,而且对干扰脉冲特别是脉冲丢失具有很强的稳健性;最后,仿真实验表明了所提方法的有效性。     

Computation and analysis of aero-optic imaging deviation of a blunt nosed aircraft with Mach number 0.5—3

Aero-optic imaging is a kind of optical effect, which describes the imaging deviation on the imaging plane. In this paper, the effect of the change of Mach number of blunt aircraft on the aero-optic imaging deviation is studied. The imaging deviations of Mach number 0.5—3 are analyzed systematically. The results show that with the increase of Mach number, imaging deviation increases gradually, and the increase rate is gradually slow. Imaging deviation slope decreases gradually with the increase of Mach number, and gradually tends to be zero, suggesting that imaging deviation is not sensitive to the change of the larger Mach number. In other words, the Mach number of smaller changes can lead to larger imaging deviation. As the Mach number of the aircraft increases, the slope of the imaging offset tends to be closer and closer to 0. When the Mach number of the aircraft increases to a certain extent, the change of the imaging offset will not have much influence. Therefore, in order to reduce the impact of flight speed on imaging migration, the aircraft should fly at a higher Mach number.     

Unsupervised model-driven neural network based image denoising for transmission line monitoring

With the expansion of smart grid and Internet of things (IoT) technology, edge computing has a wide variety of applications in these domains. The criteria for real-time monitoring and accuracy are particularly high in the field of online real-time monitoring of electricity lines. Based on edge technology, high-quality real-time monitoring can be performed for transmission lines using image processing techniques. Therefore, we propose an image denoising method, which can learn clean images using a stream-based generative model. The stream model uses a two-stage approach in the network to handle the different training periods of denoising separately. Experimental results show that the proposed method has good denoising performance.     

BP神经网络结合变量选择方法在牛奶蛋白质含量检测中的应用北大核心CSCD

牛奶中的蛋白质含量会影响牛奶的品质,利用高光谱图像的光谱特征信息研究对牛奶蛋白质含量预测的可行性。本文提出一种基于竞争性自适应重加权算法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)结合多层前馈神经网络(back propagation, BP)的预测建模方法,实验以含有不同浓度蛋白质的牛奶为对象,利用可见光/近红外高光谱成像系统共采集到5种牛奶共计250组高光谱数据,通过实验对比选择采用标准化方法对获取到的吸收光谱预处理,然后采用CARS结合SPA筛选特征波长,得到18个特征波长,建立CARS-SPA-BP模型,经过试验,CARS-SPA-BP模型的训练集决定系数和测试集决定系数R;和R;分别达到0.971和0.968,训练集均方根误差(root mean square error of calibration,RMSEC)和测试集均方根误差(root mean square error of prediction,RMSEP)达到了0.033和0.034。研究发现,采用CARS结合SPA筛选的牛奶特征波长建立的多层前馈神经网络模型,其模型预测结果与全波长建模相比并没有明显降低,因此将CARS结合SPA用于波长筛选并且结合BP神经网络基本可以完成对牛奶蛋白质含量的预测。为验证CARS-SPA-BP模型的预测能力,在相同数据环境下,使用较为传统的偏最小二乘回归(partial least squares regression, PLSR)进行建模,实验结果表明,CARS-SPA-BP相较于PLSR,R;和RMSEP均有明显提升。研究表明,CARS-SPA-BP可充分利用牛奶光谱特征信息实现较高精度的牛奶蛋白质含量检测。     

海战场态势生成技术发展综述

未来的战争必将是多兵种、多域联合作战,战场态势作为未来联合作战的重要支撑,旨在为联合作战提供精准、高效的统一态势图,而如何将多平台、同/异构传感器信息及其他情报信息与战场环境融合生成准确可靠的战场态势是亟需解决的技术难题。鉴于现代海战场对高精度、强实时、全要素战场态势图的迫切需求,对海战场态势生成技术进行了综述。首先梳理了海上态势生成项目的发展历程及能力水平;然后详细介绍了通用作战图/通用战术图等典型项目,在态势生成部分中通过态势图的要素组成、态势生成流程及关键技术对态势生成技术进行了阐述;最后对未来海战场态势生成技术的发展趋势进行了预测,希望可以为态势生成相关研究提供参考。     

一种宽带注入锁定三倍频器

文章提出了一种宽带注入锁定三倍频器。在传统注入方式基础上,倍频器采用了推-推差分对输入信号进行二倍频,并将产生的二次谐波通过变压器耦合至注入管的源极共模点,增强了注入管源极共模点二次谐波。由于注入电流是由注入信号与源极共模点二次谐波进行混频而产生,因此注入电流也被增强,从而增大了锁定范围。除此之外,三倍频采用了四阶谐振器,谐振阻抗的相位在过零点被平坦化,锁定范围进一步被增大。采用标准CMOS 65 nm工艺设计三倍频,芯片面积为720×670 μm²,1.2-V供电时的功耗为15.2 mW。0 dBm注入功率下三倍频的锁定范围为19.2~27.6 GHz,对应的基波抑制比大于25 dB,二次谐波抑制大于35 dB。注入锁定三倍频器可满足5G收发机中本振源的要求。     

基于故障模式影响分析方法的脉冲行波管可靠性研究

运用故障模式影响分析方法分析了某型号脉冲行波管的主要故障模式,针对此类故障模式采取了相应的改进措施,降低了产品主要故障出现概率,提高了脉冲行波管的可靠性,同时提升了真空电子器件的产品质量。     

Research on the properties of ZnO1-xSx thin films modified by sulfur doping for CIGS solar cells

ZnO1-xSx thin films modified by sulfur doping were prepared on glass substrates by chemical bath deposition (CBD) for studying the effect of thiourea concentration on the thin film properties. The obtained ZnO1-xSx thin films were characterized by scanning electron microscopy (SEM), which shows the surfaces of ZnO1-xSx thin films deposited under the thiourea concentration of 0.14 M are more compact. X-ray diffraction (XRD) measurement shows that the ZnO1-xSx thin films with hexagonal crystal structure had strong diffraction peaks and better crystallinity. The optical transmittance of the ZnO1-xSx thin films with 0.14 M thiourea concentration is above 80% in the wavelength range of 300—900 nm. According to the measurement results from spectrophotometer, the ZnO1-xSx band gap energy value Eg varies nonlinearly with different S/(S+O) ratio x, and increases with the increase of x. There is a band gap value of 2.97 eV in the ZnO1-xSx thin films deposited under 0.14 M thiourea concentration. Therefore, the thin films have better structural, optical and electric properties, and are more suitable for the buffer layers of copper indium gallium selenide (CIGS) thin film solar cells.     

Focusing enhanced broadband metalens via height optimization

Metalenses are two-dimensional planar metamaterial lenses, which have the advantages of high efficiency and easy integration. Based on the method of spatial multiplexing, a metalens with a wide working waveband is designed by arranging TiO2 nanopillars under the resonance phase regulation. In addition, choosing an assistant metalens with optimized heights is effective to enhance metalens’s focusing, which is also illustrated in this paper. The metalens, designed with numerical aperture (NA) of 0.72 and center working wavelength of 600 nm, achieves the working waveband of 550—660 nm, the focus point’s size of below 420 nm, and the focusing efficiency of more than 30%.