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Precision integration of grating-based polarizers onto focal plane arrays of near-infrared photovoltaic detectors for enhanced contrast polarimetric imaging

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International Journal of Extreme Manufacturing 2021年第3期3卷 95-102页

作者： Bo Feng Yifang Chen Duo Sun Zongyao Yang Bo Yang Xue Li Tao Li Nanolithography and Application Research Group State Key Laboratory of ASIC and SystemSchool of Information Science and TechnologyFudan UniversityShanghai 200433People’s Republic of China State Key Laboratories of Transducer Technology Shanghai Institute of Technical PhysicsChinese Academy of SciencesShanghai 200083People’s Republic of China

Polarimetric imaging enhances the ability to distinguish objects from a bright background by detecting their particular polarization status,which offers another degree of freedom in infrared remote ***,to scale up by monolithically integrating grating-based polarizers onto a focal plane array(FPA)of infrared detectors,fundamental technical obstacles must be overcome,including reductions of the extinction ratio by the misalignment between the polarizer and the detector,grating line width fluctuations,the line edge roughness,*** paper reports the authors’latest achievements in overcoming those problems by solving key technical issues regarding the integration of large-scale polarizers onto the chips of FPAs with individual indium gallium arsenide/indium phosphide(In Ga As/In P)sensors as the basic building *** and photovoltaic chips with divisions of the focal plane of 540×4 pixels and 320×256 superpixels have been successfully *** imaging with enhanced contrast has been *** progress made in this work has opened up a broad avenue toward industrialization of high quality polarimetric imaging in infrared wavelengths.

关键词： polarimetric imaging grating based polarizer InGaAs/InP focal plane array nanofabrication

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Quality control of AIRS total column ozone data within tropical cyclones

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Frontiers of Earth Science 2016年第2期10卷 222-235页

作者： Yin LIU Xiaolei ZOU Center of Data Assimilation for Research and Application Nanjing University of Information Science & Technology Nanjing 210044 China Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology Nanjing 210044 China Earth System Science Interdisciplinary Center University of Maryland College Park MD 20740-3823 USA

The Atmospheric Infrared Sounder （AIRS） provides infrared radiance observations twice daily, which can be used to retrieve total column ozone with high spatial resolution. However, it was found that almost all of the ozone data within typhoons and hurricanes were flagged to be of bad quality by the AIRS original quality control （QC） scheme. This determination was based on the ratio of total precipitable water （TPW） error divided by TPW value, where TPW was an AIRS retrieval product. It was found that the difficulty in finding total column ozone data that could pass AIRS QC was related to the low TPW employed in the AIRS QC algorithm. In this paper, a new two-step QC scheme for AIRS total column ozone is developed. A new ratio is defined which replaces the AIRS TPW with the zonal mean TPW retrieved from the Advanced Microwave Sounding Unit. outliers when the new The first QC step is to remove ratio exceeds 33%. Linear regression models between total column ozone and mean potential vorticity are subsequently developed with daily updates, which are required for future applications of the proposed total ozone QC algorithm to vortex initialization and assimilation of AIRS data. In the second QC step, observations that significantly deviate from the models are further removed using a biweighting algorithm. Numerical results for two typhoon cases and two hurricane cases show that a large amount of good quality AIRS total ozone data is kept within Tropical Cyclones after implementing the proposed QC algorithm.

关键词： AIRS total column ozone total precipitablewater mean potential vorticity quality control

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Preliminary Analysis of PolInSAR Scattering Mechanism in Urban Areas through UAV-borne PolInSAR system

Preliminary Analysis of PolInSAR Scattering Mechanism in Urb...

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2021 CIE International Conference on Radar, Radar 2021

作者： Lv, Zexin Qiu, Xiaolan Ding, Chibiao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing China Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Aerospace Big Dara Application Technology Suzhou China Suzhou Aerospace Information Research Institute Suzhou China

ISBN: (纸本)9781665498142

Polarimetric Interferometric SAR (PolInSAR) can improve the coherence of images and it plays an important role in urban remote sensing. The explanation of its scattering mechanism is concerned by many researchers. It is always explained from the aspect of different polarization decompositions but seldom from the height of scattering centers. In this paper, a Ku-band UAV-borne PolInSAR system is used to compare the relationship of scattering centers between PolInSAR and Pauli decomposition on different artificial targets. The physical meaning of PolInSAR is preliminary analyzed and our conclusion is also verified through a C-band manned airborne PolInSAR system. © 2021 IEEE.

关键词： Pauli decomposition Polarimetric Interferometric SAR (PolInSAR) scattering center Unmanned Aerial Vehicle (UAV)

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3D Point Cloud Reconstruction of Vehicle using Inversely Mapping and Voting from CSAR Images

3D Point Cloud Reconstruction of Vehicle using Inversely Map...

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2021 CIE International Conference on Radar, Radar 2021

作者： Feng, Shanshan Lin, Yun Teng, Fei Hong, Wen Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geospatial Information Processing and Application System University of Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9781665498142

3D reconstruction of object has raised much interest in the field of SAR. The feature of target at multi aspect angles can be obtained from sub-aperture images provided by circular SAR(CSAR), which is conducive to 3D reconstruction. Radargrammetric method is a conventional way to extract DEM while its performance for 3D reconstruction is limited by the image registration. It is difficult to find corresponding points in different sub-aperture images. In this paper, we proposed a method for 3D reconstruction of vehicle based on projections in sub-aperture images. According to the imaging mechanism of CSAR, different targets located on the same iso-range line in the zero doppler plane fall into the same cell. For a projection point, given a series of offsets, the projection point will be mapped inversely to the 3D mesh along the iso-range line. We can obtain candidates of the target. The intersection of iso-range lines can be regarded as voting process. For a candidate, the more times of intersection, the higher the number of votes, and the candidate point will be reserved. This fully excavates the information contained in the angle dimension of CSAR. The proposed approach is verified by the Gotcha Volumetric SAR Data Set. © 2021 IEEE.

关键词： Circular synthetic aperture radar(CSAR) Inversely mapping Iso-range line Three dimensional(3D) reconstruction Voting

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Cross-lingual prompt and knowledge enhancement-based named entity recognition for low-resource electronic medical records

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Neurocomputing 2025年 640卷

作者： Wang, Yurong Lin, Min Hu, Qitu Bai, Shuangcheng Li, Yanling Bao, Longjie College of Mathematics Science Inner Mongolia Normal University Inner Mongolia Hohhot010022 China Center for Applied Mathematics Inner Mongolia Inner Mongolia Hohhot010022 China Key Laboratory of Infinite-dimensional Hamiltonian System and Its Algorithm Application Ministry of Education Inner Mongolia Hohhot010022 China College of Computer Science and Technology Inner Mongolia Normal University Inner Mongolia Hohhot010022 China International Mongolian Hospital of Inner Mongolia Inner Mongolia Hohhot010020 China Inner Mongolia Electronic Information Vocational Technical College Inner Mongolia Hohhot010070 China

Pre-trained language models (PLMs) have rapidly evolved and show impressive performance in downstream tasks involving high-resource languages. However, these methods are insufficient in domain-specific tasks (e.g., medical entity recognition) involving low-resource languages (e.g., Mongolian). i. Mongolian is a low-resource language with complex word formation rules and a high degree of adhesion. ii. The clinical annotation data of Mongolian medicine are very scarce and difficult to annotate, leading to double-low-resource scenarios. Recently, prompt learning has shown good performance with PLMs, especially in small-sample scenarios. However, the impressive performance of prompt learning relies on the a priori knowledge of PLMs, and training a PLM for a vertical domain in such double-low-resource scenarios is difficult. Additionally, prompt design is a complex process requiring extensive expertise and considerable time for optimisation and refinement. In this paper, we propose a cross-lingual prompt and knowledge enhancement model based on named entity recognition for use with low-resource electronic medical records (CLPKB). First, word embeddings for source language prompts and data are mapped to target language vector space through a cross-lingual mapping matrix to reduce the spatial distance between the source and target languages. Then, cross-lingual soft prompts are used to transfer rich semantic features from the source to the target language to reduce the data dependence of the model. Meanwhile, external knowledge bases are utilised to enhance the contextual representations of the cross-lingual prompts to capture more domain-specific knowledge. The results show that our model improved by an average of 5.87% over the state-of-the-art baseline models. © 2025

关键词： Knowledge acquisition

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Spectral Characteristics and Model Inversion of Common Greening Plants in Guangzhou Under Dust Pollution 7th

Spectral Characteristics and Model Inversion of Common Green...

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7th International Conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st International Conference on geospatial Artificial Intelligence for Urban Computing, GeoAI 2019

作者： Zhang, Chen Zhou, Xia Li, Yong Yang, Ji Yang, Chuanxun Wen, Kaixiang Chen, Yuchan Yang, Libo Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangzhou510070 China Guangzhou511458 China State Grid Hunan Maintenance Company Hengyang421000 China

ISBN: (纸本)9789811561054

Hyperspectral remote sensing provides a highly efficient, convenient, and non-destructive technical means for the quantitative study of the dust retention content (DRC) of plants. Based on the common greening plants in Guangzhou, this study used hyperspectral technology to explore the spectral characteristics of different plant leaves under dust pollution, and used the Pearson correlation method to construct the DRC estimation models of plants. The results show that the spectral characteristics of the dust-retention effect of plants are mainly concentrated in the visible and near-infrared wavelengths (350–1360 nm), which are important band intervals for the study of spectral characteristics and the inversion band selection. The first derivative of spectral reflectance is more suitable for constructing the DRC estimation model than the spectral reflectance, and CF has a good fitting effect, and the deviation between the Model estimated DRC and the measured DRC is small, and its R2 is 0.55 and the RMSE is 0.300 g/m2. Through this research, the application of hyperspectral remote sensing technology in the dust retention effect research of plants can be effectively promoted, which can help to quickly and non-destructively evaluate the DRC of plants, and provide a scientific basis for rational selection of green plant types and urban air quality monitoring, and lay a foundation for large-scale DRC estimation. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Reflection

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Static Background Imaging and Moving Target Signature Removal in Multiaspect SAR Image 6

Static Background Imaging and Moving Target Signature Remova...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Shen, Wenjie Hong, Wen Han, Bing Wang, Yanping Lin, Yun Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing China Beijing China Beijing China North China University of Technology Beijing China

ISBN: (纸本)9781728129129

Multiaspect SAR has capability of providing high resolution image of static scene due to its long aperture feature. However, moving target can generate long and complex image trace in Multiaspect SAR, which may hamper the applications like SAR image interpretation and target detection. In this paper, two methods are proposed to remove moving target signature in single channel multiaspect SAR image. The two methods are all based on logarithm background subtraction. The first one is a fast scheme with cost of reduced resolution, while the second one focus on providing the high resolution but it takes more time than previous one. The first method utilize fact of target signal position changes in subaperture image sequence to obtain the static background image. The second method combines the detection results to exclude the moving target signal in each subaperture image. Then obtain the high resolution of static background by coherent summation. The methods are validated by both airborne SAR data. © 2019 IEEE.

关键词： Synthetic aperture radar

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Improved S2ANet based on attention mechanism for small target detection in remote sensing images

Improved S2ANet based on attention mechanism for small targe...

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2021 CIE International Conference on Radar, Radar 2021

作者： Lu, Dongdong Tie, Wenjie Lei, Songlin Qiu, Xiaolan Suzhou Aerospace Information Research Institute Laboratory of Spatial Information Intelligent Processing System Suzhou China Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Beijing China

ISBN: (纸本)9781665498142

Deep learning has achieved remarkable results in the field of target detection and recognition. For small targets in images, image pyramid can be used to fuse multi-scale features to improve detection performance. However, when test on remote sensing images, it is found that some important small goals will still be missed. Aiming at the problems of small target detection in remote sensing images, this paper proposes two S2ANet improved network variants based on the attention mechanism for synthetic aperture radar(SAR) payload and optical payload: for SAR images, CBAM(Convolutional Block Attention Module) attention is added to the backbone network to increase the attention of the feature extraction network for small targets in the channel and space dimensions;For optical images, firstly increase the CBAM channel attention and spatial attention in the backbone, secondly, the SE(Squeeze And Excitation) channel attention is added to the input features before the channel dimension fusion of the pyramid structure, then the attention-enhanced targets are fully integrated through up-sampling and horizontal splicing operations to improve the missed alarm rate and recall rate of small remote sensing targets. Finally, a comparative verification was carried out on the constructed airborne KU-band SAR data set and the optical remote sensing aircraft data set composed of some DOTA1.5 and FAIR1M data sets. The experimental results proved that the designed two variant networks can be used for small remote sensing. There have been certain improvements in the missed alarm rate, accuracy rate, and recall rate of the target. © 2021 IEEE.

关键词： Radar remote sensing Radar detection Object detection Radar imaging Optical imaging Feature extraction Adaptive optics

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Radial Velocity Ambiguity Resolution Method in Azimuth Multichannel HRWS SAR

Radial Velocity Ambiguity Resolution Method in Azimuth Multi...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yang, Junying Qiu, Xiaolan Shang, Mingyang Zhong, Lihua Lv, Yini Ding, Chibiao Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China Aerospace Information Research Institute Chinese Academy of Sciences National Key Laboratory of Microwave Imaging Technology Beijing China

ISBN: (纸本)9781665498142

For moving targets in synthetic aperture radar (SAR) images, the obvious features are defocusing and dislocation. To estimate motion parameters accurately is a premise for the precise imaging of moving targets. However, when the radial velocity of the target exceeds the maximum detectable unambiguous velocity, the estimated value by the existing methods is no longer the real value. A radial velocity ambiguity resolution method based on Imaging Space-Time Adaptive Processing (ISTAP) is proposed in this paper. The proposed method has no search or iterative process and is suitable for the azimuth multichannel SAR with low pulse repetition frequency (PRF). Finally, the simulated data from an x-band azimuth six-channel SAR system verify the feasibility of the proposed method. © 2021 IEEE.

关键词： azimuth multichannel SAR HRWS moving target radial velocity ambiguity

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Target Amplitude Characteristic Analysis With Neighborhood information Using C-band Circular SAR Data

Target Amplitude Characteristic Analysis With Neighborhood I...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yue, Xiaoyang Teng, Fei Lin, Yun Hong, Wen Areospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Spatial Information Processing and Application System Technology Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (纸本)9781665498142

The circular synthetic aperture radar (SAR) can observe the experimental scene from all angles. The backscatter intensity of the target in the scene can be obtained. Different targets in the imaging scene show different amplitude characteristics. For example, significant targets such as buildings and oil tanks show strong response characteristics at certain angles, and secondly, weak response characteristics for targets is shown such as grass and ground. In this article, the omnidirectional scattering intensity data of the target obtained from the radar is used to analyze the amplitude characteristics, and the model is established for different targets to obtain the final result. The fuzzy C-means (FCM) model combined with neighborhood information is used to analyze the target amplitude characteristics. The amplitude characteristics of the target are divided into two categories: strong response and weak response for analysis. The initial two types of cluster centers are set for iteration and finally the target amplitude characteristic reference values at different angles are obtained. C-band circular SAR data is used to validate our method. As a result, the amplitude characteristics of the whole scene using membership degree can be described. © 2021 IEEE.

关键词： amplitude circular FCM neighborhood target

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