小像元量子阱FPA抗光学串音的FDTD仿真

采用光栅耦合结构的焦平面阵列(Focal Plane Array,FPA)在工艺上难以制备,反射耦合结构较为容易。为探究反射耦合结构是否可以在小尺寸范围内替代光栅耦合结构,文章使用FDTD电磁场仿真软件MEEP构建了光栅耦合结构和反射结构GaAs/AlGaAs量子阱红外焦平面阵列三像元模。通过对器件内部光学串音进行仿真,验证了在逼近衍射极限时,采用全内反射结构的FPA在5~7μm和8.5~10μm之间的抗串音效果强于光栅耦合结构,而在6.5~8.5μm和10~12μm之间,光栅耦合结构的抗串音效果更好,在12~15μm范围内,两种结构的抗串音能力相当。针对15μm中心距全内反射结构量子阱FPA,探究了反射角度、刻蚀深度和量子阱周期对其串音的影响。     

一种应用于5G毫米波通信的双极化有源相控阵模组

针对5G毫米波通信,研制了一种双极化有源相控阵天线模组。厚度为2 mm的多层PCB正面印制阵列天线,在其背面集成多通道波束成形芯片,通过中间层实现天线与芯片的互连以及供电、控制等。测试结果表明,研制的板状4×4双极化相控阵模组在E面和H面均实现了不小于±40度的波束扫描范围（不大于3 dB的电平下降）和低于-18 dB的归一化交叉极化电平,在24～27.5 GHz的频率范围内实现了V极化和H极化分别为42.6～45.7 dBm和43.5～46.1 dBm的等效全向辐射功率（EIRP）。     

基于双解码路径DD-UNet的脑肿瘤图像分割算法

针对医学图像中病灶区域尺度不一、边界模糊和周围组织强度不均匀所导致的分割精度降低问题,提出了一种基于双解码器的脑肿瘤图像分割模型。为了增强特征的表征力,提出了高阶微分残差模块并使用不同空洞率的扩张卷积用于提取特征编码,提高了网络模型的分割性能;引入上下文语义信息感知模块(multi scale dilation, MSD),从不同的目标尺度中提取更多的精细信息,提高了对结构细节信息的捕获能力,同时减少了编解码器之间的特征差异;在空间解码路径中使用选择性聚合空间注意力模块(spatial aggregation attention module, SAAM),增加了对有效空间特征的权重比例,减少了无效的特征干扰。在脑肿瘤数据集上进行了实验验证,实验结果表明,所提算法的Dice系数、平均交并比、敏感性、特异性、准确率等指标分别为：93.35%、90.71%、91.15%、99.94%、96.75%。     

基于改进3D UNet的前列腺MR图像分割

针对前列腺磁共振 (magnetic resonance, MR)图像边缘模糊、对比度较低,灰度值分布不均衡而导致分割精度较差的问题,提出了一种结合双路径注意力(dual path attention,DPA) 和多尺度特征聚合(multi-scale feature aggregation,MFA) 模块的改进3D UNet网络模型。首先,对数据集进行重采样和裁剪处理以适应模型输入。然后,在3D UNet网络的编码器各层引入DPA 并添加残差连接,加强特征的 编码能力。同时,在网络解码器中加入MFA模块,以充分利用空间上下文信息,增强语义信息。最后,在公开数据集PROMISE12上进行验证,所提出的模型的Dice系数为89.90%,Hausdorff 距离为9.37 mm。相比较于其他模型,所提出模型的分割结果更优,且参数量和运算量更少。     

Real-time 3D multi-pedestrian detection and tracking using 3D LiDAR point cloud for mobile robot

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.     

ESPAR array design for the UHF RFID wireless sensor communication system

In this paper, in order to improve the received signal strength (RSS) and signal quality, three arrays of electronically steerable parasitic array radiator (ESPAR) antennas are suggested for the ultra-high frequency (UHF) radio frequency identification (RFID) communication and sensing system applications. Instead of the single antenna, the array antennas have recently been widely used in many communication systems because of their peak gains, better radiation patterns, and higher radiation efficiency. Also, there are some important issues to use the antenna array like high data rates in wireless communication systems and to better understand the many targets or sensors. In this article, a wireless sensor network (WSN) is being investigated to overcome multipath fading and interference by antenna nulling technology that can be achieved through beam control ESPAR array antennas. The proposed ESPAR array antennas exhibit higher gains like 9.63, 10.2, and 12 dBi and proper radiation patterns from one array to another. Moreover, we investigate the mutual coupling effect on the performance of array antennas with different spacing (0.5λ, 0.75λ, λ) and configurations. It is found that the worst mutual coupling reduced by −28 to −34 dB for 2 × 2 array, −3 to −43 dB for 2 × 3 array, and finally −42 dB to −51 dB due to the antenna spacing from 0.5λ to λ. Thus, these suggested antennas could effectively be applied in the WSN communication systems, internet of things (IoT) networks, and massive wireless and backscatter communication systems.     

基于分段电容阵列的改进型逐次逼近型ADC

为缩短高速模数转换器(ADC)中高位(MSB)电容建立时间以及减小功耗,提出了一种基于分段式电容阵列的改进型逐次逼近型(SAR)ADC结构,通过翻转小电容阵列代替翻转大电容阵列以产生高位数字码,并利用180 nm CMOS工艺实现和验证了此ADC结构。该结构一方面可以缩短产生高位数码字过程中的转换时间,提高量化速度;另一方面其可以延长大电容的稳定时间,减小参考电压的负载。通过缩小比较器输入对管的面积以减小寄生电容带来的误差,提升高位数字码的准确度。同时,利用一次性校准技术减小比较器的失配电压。最终,采用180 nm CMOS工艺实现该10 bit SAR ADC,以验证该改进型结构。结果表明,在1.8 V电源电压、780μW功耗、有电路噪声和电容失配情况下,该改进型SAR ADC得到了58.0 dB的信噪失真比(SNDR)。     

一种Ku波段综合馈电多功能板的研制

基于多层微波数字复合基板层叠互联技术,研制的Ku波段综合馈电多功能板集成了射频收发网络、电源分配网络、阵面波控及波控分配网络,主要负责16个片式T/R组件的功率分配与合成,同时为各T/R组件提供电源及控制信号。文中对多功能板的架构设计、工作原理进行了说明,重点介绍了各微波垂直互联电路和射频收发网络的设计,最后加工并测试了验证样件,测试结果良好。收发网络总口驻波＜1.9,分口驻波＜1.3,插损＜16 dB,相邻端口的隔离度＞20 dB,且幅度一致性≤0.602 dB,相位一致性≤6.429°。工程应用可行性和实用性得到了验证。     

基于超像素级卷积神经网络的多聚焦图像融合算法

该文提出了基于超像素级卷积神经网络(sp-CNN)的多聚焦图像融合算法。该方法首先对源图像进行多尺度超像素分割,将获取的超像素输入sp-CNN,并对输出的初始分类映射图进行连通域操作得到初始决策图;然后根据多幅初始决策图的异同获得不确定区域,并利用空间频率对其再分类,得到阶段决策图;最后利用形态学对阶段决策图进行后处理,并根据所得的最终决策图融合图像。该文算法直接利用超像素分割块进行图像融合,其相较以往利用重叠块的融合算法可达到降低时间复杂度的目的,同时可获得较好的融合效果。     

Synthesis of mono meso-pyridyl 21,23-dithiaporphyrins and unsymmetrical non-covalent porphyrin dimers

A new method has been developed to synthesize 21,23-dithiaporphyrins having one pyridyl group at the meso position. The method required easily available unknown precursors and the condensation resulted in mono meso-pyridyl 21,23-dithiaporphyrins as single products in 8-11% yield. Two of the three mono meso-pyridyl N₂S₂ porphyrins were used to synthesize non-covalent unsymmetrical porphyrin dimers containing one N₂S₂ and one N₄ porphyrin cores.