<div style="text-align:justify;"> Transceiver module and two-dimensional sum difference network are important components of phased array antenna. In this paper, multilayer printed board is used to inte...<div style="text-align:justify;"> Transceiver module and two-dimensional sum difference network are important components of phased array antenna. In this paper, multilayer printed board is used to integrate millimeter wave multi-channel transceiver circuit and sum difference network. The interconnection between them is realized through RF coaxial vertical transition. At the same time, the heat dissipation design and inter channel shielding design of the module are carried out. The RF and low frequency required by the module are completed through the wiring between and within the dielectric plate layers. Finally, 128 arrays are fabricated and verified by multi-channel passive test. The results show that the type transceiver module integrating with two-dimensional sum difference network has good performance, and 128 channels have excellent amplitude and phase characteristics. The integration technology has the characteristics of lightweight, miniaturization, high integration and low manufacturing cost. It can be widely used in miniaturized phased array antennas. </div>展开更多
In this paper, the design of a planar ultra-broadband sum-and-difference network is pre-sented. This network employs a novel power divider and anti-phase balun as a building block. An equivalent 180o coupler with a ba...In this paper, the design of a planar ultra-broadband sum-and-difference network is pre-sented. This network employs a novel power divider and anti-phase balun as a building block. An equivalent 180o coupler with a bandwidth of 6.2～14GHz is achieved by back-connecting the power divider and balun together. Four such couplers are connected to form an ultra-broadband sum-and-difference network which has a bandwidth of 91%. This network, with insertion loss less than 1.8dB in sum port and nulls less than -20dB in all delta ports, is verified to be excellent, resulting in the advantages of being compact, easy manufacturing and low cost.展开更多
As the basis of machine vision,the biomimetic image sensing devices are the eyes of artificial intelligence.In recent years,with the development of two-dimensional(2D)materials,many new optoelectronic devices are deve...As the basis of machine vision,the biomimetic image sensing devices are the eyes of artificial intelligence.In recent years,with the development of two-dimensional(2D)materials,many new optoelectronic devices are developed for their outstanding performance.However,there are still little sensing arrays based on 2D materials with high imaging quality,due to the poor uniformity of pixels caused by material defects and fabrication technique.Here,we propose a 2D MoS_(2)sensing array based on artificial neural network(ANN)learning.By equipping the MoS_(2)sensing array with a“brain”(ANN),the imaging quality can be effectively improved.In the test,the relative standard deviation(RSD)between pixels decreased from about 34.3%to 6.2%and 5.49%after adjustment by the back propagation(BP)and Elman neural networks,respectively.The peak signal to noise ratio(PSNR)and structural similarity(SSIM)of the image are improved by about 2.5 times,which realizes the re-recognition of the distorted image.This provides a feasible approach for the application of 2D sensing array by integrating ANN to achieve high quality imaging.展开更多
为解决弱光照条件下红外与可见光图像融合质量差的问题,提出一种结合亮度感知与密集卷积的红外与可见光图像融合方法(brightness perception and dense convolution,BPD-Fusion)。首先,对可见光图像进行亮度计算,得到亮度权重并对其暗...为解决弱光照条件下红外与可见光图像融合质量差的问题,提出一种结合亮度感知与密集卷积的红外与可见光图像融合方法(brightness perception and dense convolution,BPD-Fusion)。首先,对可见光图像进行亮度计算,得到亮度权重并对其暗区域进行亮度增强;然后,将增强的可见光图像与红外图像级联输入生成器,在其Conv1阶段后嵌入密集卷积以获取更丰富的图像特征;最后,为了达到较强的图像重构与生成能力,建立多损失函数构建端到端的图像融合过程。在TNO和KAIST数据集上进行融合质量测评:主观评价上,提出的方法视觉效果良好;客观评价上,差异相关和、信息熵、互信息和平均梯度指标均优于对比方法。展开更多
文摘<div style="text-align:justify;"> Transceiver module and two-dimensional sum difference network are important components of phased array antenna. In this paper, multilayer printed board is used to integrate millimeter wave multi-channel transceiver circuit and sum difference network. The interconnection between them is realized through RF coaxial vertical transition. At the same time, the heat dissipation design and inter channel shielding design of the module are carried out. The RF and low frequency required by the module are completed through the wiring between and within the dielectric plate layers. Finally, 128 arrays are fabricated and verified by multi-channel passive test. The results show that the type transceiver module integrating with two-dimensional sum difference network has good performance, and 128 channels have excellent amplitude and phase characteristics. The integration technology has the characteristics of lightweight, miniaturization, high integration and low manufacturing cost. It can be widely used in miniaturized phased array antennas. </div>
文摘In this paper, the design of a planar ultra-broadband sum-and-difference network is pre-sented. This network employs a novel power divider and anti-phase balun as a building block. An equivalent 180o coupler with a bandwidth of 6.2～14GHz is achieved by back-connecting the power divider and balun together. Four such couplers are connected to form an ultra-broadband sum-and-difference network which has a bandwidth of 91%. This network, with insertion loss less than 1.8dB in sum port and nulls less than -20dB in all delta ports, is verified to be excellent, resulting in the advantages of being compact, easy manufacturing and low cost.
基金This project was financially supported by the Dalian Science and Technology Innovation Fund of China(No.2019J11CY011)the Science Fund for Creative Research Groups of NSFC(No.51621064).
文摘As the basis of machine vision,the biomimetic image sensing devices are the eyes of artificial intelligence.In recent years,with the development of two-dimensional(2D)materials,many new optoelectronic devices are developed for their outstanding performance.However,there are still little sensing arrays based on 2D materials with high imaging quality,due to the poor uniformity of pixels caused by material defects and fabrication technique.Here,we propose a 2D MoS_(2)sensing array based on artificial neural network(ANN)learning.By equipping the MoS_(2)sensing array with a“brain”(ANN),the imaging quality can be effectively improved.In the test,the relative standard deviation(RSD)between pixels decreased from about 34.3%to 6.2%and 5.49%after adjustment by the back propagation(BP)and Elman neural networks,respectively.The peak signal to noise ratio(PSNR)and structural similarity(SSIM)of the image are improved by about 2.5 times,which realizes the re-recognition of the distorted image.This provides a feasible approach for the application of 2D sensing array by integrating ANN to achieve high quality imaging.
文摘为解决弱光照条件下红外与可见光图像融合质量差的问题,提出一种结合亮度感知与密集卷积的红外与可见光图像融合方法(brightness perception and dense convolution,BPD-Fusion)。首先,对可见光图像进行亮度计算,得到亮度权重并对其暗区域进行亮度增强;然后,将增强的可见光图像与红外图像级联输入生成器,在其Conv1阶段后嵌入密集卷积以获取更丰富的图像特征;最后,为了达到较强的图像重构与生成能力,建立多损失函数构建端到端的图像融合过程。在TNO和KAIST数据集上进行融合质量测评:主观评价上,提出的方法视觉效果良好;客观评价上,差异相关和、信息熵、互信息和平均梯度指标均优于对比方法。
