High resolution range profile analysis based on multicarrier phase-coded waveforms of OFDM radar

Orthogonal frequency division multiplexing（OFDM） radar with multicarrier phase-coded waveforms has been recently introduced to achieve high range resolution.The conventional method for obtaining the high resolution range profile（HRRP） is based on matched filters.A method of synthesizing HRRP based on the fast Fourier transform（FFT） and decoding is proposed.The mathematical expressions of HRRP are derived by assuming an elementary scenario of point-scattering targets.Based on the characteristic of OFDM multicarrier signals,it mainly analyzes the influence on HRRP exerted by several factors,such as velocity compensation errors,the sampling frequency offset,and so on.The conclusions are significant for the design of the OFDM imaging radar.Finally,the simulation results demonstrate the validity of the conclusions.

Improving the Angular Resolution of Coded-Mask Telescopes by Direct Demodulation

We develop a new procedure to improve the angular resolution of coded-mask telescopes by the Direct Demodulation Method （DDM）. DDM has been applied to both real and simulated data of INTEGRAL/IBIS. The angular resolution of IBIS/ISGRI has been improved from about 13＇ to 2＇.

A HIGH RESOLUTION WIDE SWATH SAR METHOD BASED ON INTRA-PULSE NULL STEERING AND MIMO

High Resolution Wide Swath (HRWS) Synthetic Aperture Radar (SAR) often suffers from low Signal-to-Noise Ratio (SNR) due to small transmitting antenna, especially in phased array antenna systems. Digital Beam Forming (DBF) based on Single Input and Multiple Output (SIMO) achieves receiving array gain at the cost of increasing data rate. This letter proposes a new HRWS SAR method, which employs intra-pulse null steering to get receiving gain in elevation and decrease the data rate, and Multiple Input and Multiple Output (MIMO) using Space-Time Block Coding (STBC) in azimuth to get transmitting gain and receiving array gain simultaneously. The feasibility is verified by deduction and simulations.

Virtual Anatomy: The Dissecting Theatre of the Future—Implementation of Cinematic Rendering in a Large 8 K High-Resolution Projection Environment

Modern computer techniques have been in use for several years to generate three-dimensional visualizations of human anatomy. Very good 3-D computer models of the human body are now available and used routinely in anatomy instruction. These techniques are subsumed under the heading “virtual anatomy” to distinguish them from the conventional study of anatomy entailing cadavers and anatomy textbooks. Moreover, other imaging procedures (X-ray, angiography, CT and MR) are also used in virtual anatomy instruction. A recently introduced three-dimensional post-processing technique named Cinematic Rendering now makes it possible to use the output of routine CT and MR examinations as the basis for highly photo-realistic 3-D depictions of human anatomy. We have installed Cinematic Rendering (enabled for stereoscopy) in a high-definition 8K 3-D projection space that accommodates an audience of 150. The space’s projection surface measures 16 × 9 meters;images can be projected on both the front wall and the floor. A game controller can be used to operate Cinematic Rendering software so that it can generate interactive real-time depictions of human anatomy on the basis of CT and MR data sets. This prototype installation was implemented without technical problems;in day-to-day, real-world use over a period of 22 months, there were no impairments of service due to software crashes or other technical problems. We are already employing this installation routinely for educational offerings open to the public, courses for students in the health professions, and (continuing) professional education units for medical interns, residents and specialists—in, so to speak, the dissecting theater of the future.

Resolution Characteristics of GaAs/GaAlAs Transmission Photocathode

The resolution characteristic of GaAs/GaAlAs transmission photocathode is an important parameter in third generation intensifiers. The modulation transfer function of GaAs/GaAlAs transmission photocathode is derived from a simple two-dimensional diffusion equation. The theoretical resolution characteristic of a 2 μm thick GaAs/GaAlAs transmission photocathode is calculated. The relationship between resolution and parameters in GaAs/GaAlAs transmission photocathode is discussed. A conclusion is shown that one can design the GaAs/GaAlAs transmission photocathode for maximum quantum efficiency, since the sacrifice in the resolution doesn't limit system performances.

A MULTI-RESOLUTION SPECTRUM SENSING (MRSS) SCHEME UNDER MEASUREMENT-BASED CHANNEL MODELS IN COGNITIVE RADIO

Spectrum sensing is one of the key technologies in Cognitive Radios(CRs).Previous works are accomplished under simple channel models,which may lead to unreliable results when it applied to the over-the-air systems.In this paper,we investigate the performance of a Multi-Resolution Spectrum Sensing(MRSS) algorithm under measurement-based channel models in China.MRSS is a wavelet based algorithm which is suitable for non-stationary,wideband signal analysis.Using statistical mod-eling,measurement-based channel models are presented under typical urban and suburban scenarios in Shanghai,China.Then,the performance of the MRSS algorithm is evaluated under the measure-ment-based channel models.Simulation results show that,using MRSS,the performance is always better in the scenarios where Line-Of-Sight(LOS) path exist;also,in LOS scenarios,rich scattering effect helps to increase the performance.

MODIS image super-resolution via learned topic dictionaries and regression matrices

Moderate resolution imaging spectroradiometer(MODIS) imaging has various applications in the field of ground monitoring,cloud classification and meteorological research.However,the limitations of the sensors and external disturbance make the resolution of image still limited in a certain level.The goal of this paper is to use a single image super-resolution(SISR) method to predict a high-resolution(HR) MODIS image from a single low-resolution(LR) input.Recently,although the method based on sparse representation has tackled the ill-posed problem effectively,two fatal issues have been ignored.First,many methods ignore the relationships among patches,resulting in some unfaithful output.Second,the high computational complexity of sparse coding using l_1 norm is needed in reconstruction stage.In this work,we discover the semantic relationships among LR patches and the corresponding HR patches and group the documents with similar semantic into topics by probabilistic Latent Semantic Analysis(p LSA).Then,we can learn dual dictionaries for each topic in the low-resolution(LR) patch space and high-resolution(HR) patch space and also pre-compute corresponding regression matrices for dictionary pairs.Finally,for the test image,we infer locally which topic it corresponds to and adaptive to select the regression matrix to reconstruct HR image by semantic relationships.Our method discovered the relationships among patches and pre-computed the regression matrices for topics.Therefore,our method can greatly reduce the artifacts and get some speed-up in the reconstruction phase.Experiment manifests that our method performs MODIS image super-resolution effectively,results in higher PSNR,reconstructs faster,and gets better visual quality than some current state-of-art methods.

Application of Sparse-Coding Super-Resolution to 16-Bit DICOM Images for Improving the Image Resolution in MRI

Purpose: To improve the image resolution of magnetic resonance imaging (MRI), conventional interpolation methods are commonly used to magnify images via various image processing approaches;however, these methods tend to produce artifacts. While super-resolution (SR) schemes have been introduced as an alternative approach to apply medical imaging, previous studies applied SR only to medical images in 8-bit image format. This study aimed to evaluate the effectiveness of sparse-coding super-resolution (ScSR) for improving the image quality of reconstructed high-resolution MR images in 16-bit digital imaging and communications in medicine (DICOM) image format. Materials and Methods: Fifty-nine T1-weighted images (T1), 84 T2-weighted images (T2), 85 fluid attenuated inversion recovery (FLAIR) images, and 30 diffusion-weighted images (DWI) were sampled from The Repository of Molecular Brain Neoplasia Data as testing datasets, and 1307 non-medical images were sampled from the McGill Calibrated Color Image Database as a training dataset. We first trained the ScSR to prepare dictionaries, in which the relationship between low- and high-resolution images was learned. Using these dictionaries, a high-resolution image was reconstructed from a 16-bit DICOM low-resolution image downscaled from the original test image. We compared the image quality of ScSR and 4 interpolation methods (nearest neighbor, bilinear, bicubic, and Lanczos interpolations). For quantitative evaluation, we measured the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). Results: The PSNRs and SSIMs for the ScSR were significantly higher than those of the interpolation methods for all 4 MRI sequences (PSNR: p p Conclusion: ScSR provides significantly higher image quality in terms of enhancing the resolution of MR images (T1, T2, FLAIR, and DWI) in 16-bit DICOM format compared to the interpolation methods.

Performance Evaluation of Super-Resolution Methods Using Deep-Learning and Sparse-Coding for Improving the Image Quality of Magnified Images in Chest Radiographs

Purpose: To detect small diagnostic signals such as lung nodules in chest radiographs, radiologists magnify a region-of-interest using linear interpolation methods. However, such methods tend to generate over-smoothed images with artifacts that can make interpretation difficult. The purpose of this study was to investigate the effectiveness of super-resolution methods for improving the image quality of magnified chest radiographs. Materials and Methods: A total of 247 chest X-rays were sampled from the JSRT database, then divided into 93 training cases with non-nodules and 154 test cases with lung nodules. We first trained two types of super-resolution methods, sparse-coding super-resolution (ScSR) and super-resolution convolutional neural network (SRCNN). With the trained super-resolution methods, the high-resolution image was then reconstructed using the super-resolution methods from a low-resolution image that was down-sampled from the original test image. We compared the image quality of the super-resolution methods and the linear interpolations (nearest neighbor and bilinear interpolations). For quantitative evaluation, we measured two image quality metrics: peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). For comparative evaluation of the super-resolution methods, we measured the computation time per image. Results: The PSNRs and SSIMs for the ScSR and the SRCNN schemes were significantly higher than those of the linear interpolation methods (p p p Conclusion: Super-resolution methods provide significantly better image quality than linear interpolation methods for magnified chest radiograph images. Of the two tested schemes, the SRCNN scheme processed the images fastest;thus, SRCNN could be clinically superior for processing radiographs in terms of both image quality and processing speed.

论环境纠纷非诉解决机制的专门化与法典回应

环境纠纷的特殊性与环境责任的专门性要求环境纠纷非诉解决机制应在传统方式的基础上进行专门化构建。国外的环境纠纷非诉解决机制的专门化主要体现为专门的环境纠纷行政处理机制、专门法院附设ADR机制、专门的民间性环境ADR机制三种样态。我国的环境纠纷非诉解决机制专门化应朝着引入中立评估、重塑环境纠纷行政处理、激活环境仲裁、健全生态磋商、探索设立新型环境ADR机构等方向努力。同时,在生态环境法典编纂的背景下,环境纠纷非诉解决机制专门化也应在法典中得到回应,明确专门化的基本内容和形式。

基于Barker码脉冲压缩技术的钢板多阵元Lamb波电磁超声换能器设计与优化

为了解决传统Barker码脉冲压缩技术受脉冲功率放大器额定参数(占空比,最大脉冲宽度等)限制而导致的脉冲压缩效果下降、检测速度降低等问题,提出一种基于Barker码脉冲压缩技术的多阵元Lamb波电磁超声换能器(EMAT)。建立了基于tone-burst信号激励-Barker码脉冲压缩技术的多阵元Lamb波EMAT检测过程的有限元模型,分析了永磁体的配置形式、阵元序列长度、激励信号周期数、曲折线圈匝数等因素对脉冲压缩后的主旁瓣比和主瓣宽度的影响,并进行了实验验证。结果表明:曲折线圈匝数为4和Barker码序列长度为13位的多阵元EMAT在配置3对外置永磁体后,其信噪比(SNR)可提高9.8 dB。综合考虑检测回波的空间分辨率和SNR,多阵元Lamb波EMAT最佳参数为:曲折线圈匝数为10、激励信号周期数为11、Barker序列为13位,并配置3对外置永磁体。

CR双下肢全长图像拼接的摄影参数探讨及其临床应用价值

目的:探讨CR在双下肢全长图像拼接的摄影参数及临床应用价值。方法:以FCR-5000CR成像系统的应用及CR在骨骼系统摄影条件的成像特性来选择合适的下肢全长骨骼数字化X线的摄影条件。结果:根据不同摄影参数下的空间分辨率分布情况,获取优化的CR下肢全长摄影的管电压和管电量参数。结论:CR在双下肢全长的摄影参数应根据CR成像系统的特性,以实验结果为依据。在保证影像质量和患者受辐射剂量上选择最为适宜的摄影参数,为膝关节置换术等临床应用提供准确的影像学资料。

密封消解法测定高氯离子含盐废水COD_(Cr)的探讨

针对国标重铬酸钾法测定高氯离子含盐废水CODCr时的不足 ,采用密封消解法来测定高盐废水CODCr,通过丁酮氧化率、氯离子干扰、混配水样和实际水样测定结果的比较 ,对国标法和密封消解法进行了验证。试验结果表明 :在测定高氯离子含盐废水CODCr值时 ,密封消解法优于重铬酸钾法 ,能够真实准确地反映废水的CODCr。

曝光条件、IP尺寸等与CR照片影像的空间分辨力

目的 :探讨曝光条件、IP尺寸等与CR照片影像空间分辨力的关系。方法 :依据Siemens点数法曝光条件表 ,在点数不变的情况下换算出摄影部位手的数组曝光条件 ,选用四种不同尺寸的IP及大小焦点 ,分别对矩形波测试卡进行摄影。采用无放大和放大 2倍的后处理技术 ,视读并记录CR照片影像的空间分辨力数值 ,分析其影响CR照片影像空间分辨力的条件。结果 :①摄影部位、曝光条件相同 ,CR照片影像的空间分辨力 ,小焦点大于大焦点 ;②摄影部位、曝光条件及焦点大小相同 ,CR照片影像的空间分辨力随IP尺寸的增加而减小 ;③CR照片影像的空间分辨力 ,放大 2倍的照片影像明显高于无放大处理的照片影像 ;④适宜的曝光条件可提高CR照片影像的空间分辨力。结论 :影响CR照片影像空间分辨力的条件 :小尺寸IP大于大尺寸IP ;小焦点大于大焦点 ;适宜的后处理放大倍数大于无放大处理 ;适宜的曝光条件组合大于其它组合。

CR下肢全长图像拼接摄影参数的探讨

目的探讨数字化X线成像系统(CR)在下肢全长图像拼接的摄影参数。方法以FCR-5000 CR成像系统的应用及CR在骨骼系统摄影条件的成像特性,来选择合适的下肢全长骨骼数字化X线的摄影条件。结果根据不同摄影参数下的空间分辨率分布情况,获取优化的CR下肢全长摄影的管电压和毫安量参数。结论CR下肢全长图像拼接的摄影条件,应根据CR成像系统的特性,以实验结果为依据,在保证影像质量和患者受辐射剂量上选择最为适宜的摄影参数。

融合多重多尺度特征的高分辨率遥感影像建筑物提取网络

针对高分辨率遥感影像因复杂背景信息导致的建筑物边界、角点以及内部信息出现的错分、漏分问题,提出了一种融合多重多尺度目标特征的DPRS-Net深度学习网络。DPRS-Net采用Resnet50与Swin-T(Tiny)的并行编码结构以结合两种编码优势,进而获取特征图的大范围深层信息;利用跳跃连接降低建筑物的边界特征损失;引入特征金字塔注意力模块和密集空洞空间特征金字塔池化模块,使采样过程中的建筑物细节特征损失减弱。为验证模型的优势性、分析性能提升原因,在WHU和自建Changchun3建筑物数据集上进行对比和消融实验。结果表明,DPRS-Net在两种数据集上均取得更高的精度,提取的建筑物信息更为完整,且模型各结构均能有效提升预测效果。

基于频域多尺度小波变换的CR图像超分辨率增强

针对CR(Computed Radiography)成像过程中分辨率不足的问题,提出了一种基于小波变换的超分辨率增强方法。该方法通过小波分析方法对低频尺度系数进行灰度值分割,对高频小波系数进行增益操作,并给出了小波系数增强策略。对CR胸部透视图像进行算法验证的结果表明,该算法改善了图像的视觉效果,从而验证了该算法的正确性和有效性。

基于特征基的GMC卷积稀疏机械故障特征解析方法

在机械设备的复杂工况下,监测信号易受多振动源及环境噪声干扰,导致故障特征微弱且呈现强耦合特性,这给设备故障诊断带来极大挑战。因此,提出了一种基于振动特性基的GMC增强卷积稀疏机械故障特征解析方法,实现微弱耦合故障特征解析。首先,构造了一种自适应单边衰减小波匹配算法以获取最优特征原子,将最优特征原子升维同时匹配故障周期,以得到具有周期特征的振动特征基。其次,提出基于GMC增强的卷积稀疏编码,结合振动特征基优化求解稀疏系数。此外,提出了一种基于平均峭度与谐波能量比的过程参数优化选择方法,克服了优化过程中关键参数难选取的问题。最后,提取包络谱主要特征与理论故障特征频率对比判断故障类型。通过仿真分析和试验台信号验证,并对比分析了基于谱峭度分解和可调变Q因子小波变换GMC稀疏增强等两种传统方法。实验结果表明,相较于上述两种传统方法,本文提出的方法可以有效地分离不同类型的故障特征信号,并实现故障特征的增强。

高纯Fe-0.2%P-2%Cr-C合金晶界的高分辨俄歇能谱分析

利用高分辨俄歇能谱仪研究了高纯Fe 0 2 %P 2 %Cr C合金的晶界·结果表明 ,沿晶断面上有大量尺寸约 0 3 μm的颗粒状碳化物·碳化物处碳的PHR值分别为 3 4 9%和 3 3 3 % ,铬的PHR值为 1 4 6%和 7 3 % ,碳化物为富铬碳化物 ;晶界上无碳化物处存在显著的磷偏聚和碳偏聚 ,磷的平均偏聚量分别为 2 0 2 %和 1 9 6% (PHR) ,晶界富集系数为 5 6和 5 4,碳的PHR值分别为 8 6%和 1 2 6% ,晶界富集系数为 3 0 8和 45 0 ;随合金碳量增加 ,碳在晶界偏聚量增加 。

CR检测技术在长输管道上的应用

介绍了长输管道检测中使用计算机射线照相(Computered radiography,CR)技术的注意事项及要求,并以某工程管道中的CR检测为例,对底片出现的典型影像进行了分析,介绍了伪缺陷和真实缺陷的评定方法,以供同行参考。