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A Novel Gradient Descent Least-Squares (GDLSs) Algorithm for Efficient Gridless Line Spectrum Estimation With applications in Tomographic SAR Imaging

A Novel Gradient Descent Least-Squares (GDLSs) Algorithm for...

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作者： Shi, Ruizhe Zhang, Zhe Qiu, Xiaolan Ding, Chibiao University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100190 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou Jiangsu215123 China CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing100190 China

This article presents a novel efficient method for gridless line spectrum estimation problems with single snapshot and sparse signals, namely the gradient descent least-squares (GDLS) method. Conventional single-snapshot (a.k.a. single-measure vector or SMV) line spectrum estimation methods either rely on smoothing techniques that sacrifice the range and/or azimuth resolution or adopt the sparsity constraint and utilize the compressed sensing (CS) method by defining prior grids and resulting in the off-grid problem. Recently emerged atomic norm minimization (ANM) methods achieved gridless SMV line spectrum estimation, but its computational complexity is extremely high;thus, it is practically infeasible in real applications with large problem scales. Our proposed GDLS method reformulates the line spectrum estimations problem into a least-squares (LSs) estimation problem and solves the corresponding objective function via a gradient descent algorithm in an iterative fashion with efficiency. The convergence guarantee, computational complexity, and performance analysis for evenly distributed antenna array cases are discussed in this article. Numerical simulations show that the proposed GDLS algorithm outperforms the state-of-the-art methods, for example, CS and ANM, in terms of estimation performances. It can completely avoid the off-grid problem, and its computational complexity is significantly lower than ANM. Our method has been tested in tomographic SAR (TomoSAR) imaging applications via simulated and real experimental data. Results show the great potential of the proposed method in terms of better cloud point performance and eliminating the gridding effect. © 1980-2012 IEEE.

关键词： Spectrum analysis

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A Comparative Study of Single-polarized and Polarimetric SAR Images Applied on Unsupervised Classification

A Comparative Study of Single-polarized and Polarimetric SAR...

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2021 CIE International Conference on Radar, Radar 2021

作者： Qu, Junrong Qiu, Xiaolan Key Laboratory of Technology in Geospatial Information and Application System Aerospace Information Research Institute School of Electronic Electrical and Communication Engineering Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665498142

SAR image understanding is a significant but also challenging issue in practice. In order to detect the difference between single-polarized and polarimetric SAR (PolSAR) data and explore more information from the pre one, we use GF3 data for experiments and adopt the Deep Clustering with Convolutional Autoencoders (DCEC) algorithm for single-polarized SAR image unsupervised classification. Using both the Kappa coefficient and mutual information derived from the confusion matrix, the results of single-polarized SAR data and PolSAR data are compared. It shows that the classification results of single-polarized SAR data match with the polarimetric ones to some extent, and their results are comparable in some specific applications. This paper presents the potential of information mining from single-polarized SAR images, as well as gives some references for the selection and trade-off between single- and full-polarized SAR data. © 2021 IEEE.

关键词： comparison polarimetric SAR single-polarized SAR unsupervised classification

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ScanSAR Radiometric Correction and Analysis of GaoFen-3 6

ScanSAR Radiometric Correction and Analysis of GaoFen-3

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

作者： Zhong, Lihua Qiu, Xiaolan Han, Bing Hu, Yuxin Chen, Aiping DIng, Chibiao Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing100190 China Beijing Institute of Telemetry and Telecommunications Technology Beijing100094 China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129129

GaoFen-3(GF-3) is China's first multi-mode c-band radar imaging satellite launched on August 10, 2016. In order to meet the requirements for global ocean observing and wave detection, three wide swath modes were designed using Scan-beam synthetic aperture radar (ScanSAR) imaging mode, which are narrow scan, wide scan and global observation. The resolution varies from 50m to 500 m and the swath varies from 300 km to 650 km. Due to the Mosaic of sub-swath image, ScanSAR has a high requirement for radiation accuracy from processing algorithm. In this paper, GF-3 ScanSAR imaging processing gain and radiation correction methods are introduced, and the processing results of measured data collected in the amazon rainforest are analyzed to verify the radiation accuracy of accuracy ScanSAR. © 2019 IEEE.

关键词： Synthetic aperture radar

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Matrix calculation of high-dimensional cross product and its application in automatic recognition of the endmembers of hyperspectral imagary

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Science China(information Sciences) 2011年第1期54卷 197-203页

作者： GENG XiuRui1,ZHAO YongChao1,LIU SuHong2 & WANG FuXiang3 1key laboratory of technology in geo-spatial information processing and application system, Institute of Electronics,Chinese Academy of Sciences,Beijing 100080,China 2State key laboratory of Remote Sensing Science,Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing applications of Chinese Academy of Sciences, School of geography,Beijing Normal University,Beijing 100875,China 3School of Electronics and information Engineering,Beihang University,Beijing 100191,China 1. Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100080 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences School of Geography Beijing Normal University Beijing 100875 China3. School of Electronics and Information Engineering Beihang University Beijing 100191 China

This paper gives the definition of the high-dimensional cross product and its calculation by extending the 3-D cross product definition into the high-dimensional vector *** on the properties of the cross product,the volume variance index(VVI)is proposed to be used in extracting automatically the endmembers of the hypherspectral imagery which eliminates the shortcoming of the traditional method of using simplex only where the extraction results were easily impacted by the abnormal pixels.A case study of endmembers extraction experiment using the VVI method with the AVIRIS data for Cuprite has shown a very good result.

关键词： endmember simplex hyperspectral imagery cross product

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Multi-Aspect SAR Target Recognition Based on Efficientnet and GRU

Multi-Aspect SAR Target Recognition Based on Efficientnet an...

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IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Pengfei Zhao Lijia Huang Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese of Sciences Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Automatic target recognition (ATR) in synthetic aperture radar (SAR) has been extensively applied in military and civilian fields recently. However, SAR images are very sensitive to the azimuth of the imaging, and the same target at different aspects differs greatly, thus requiring more reliable and robust multi-aspect ATR recognition performance. In this paper, we propose an end-to-end multi-aspect ATR model based on EfficientNet and GRU, and use island loss as the training loss, which is more suitable for SAR ATR. Experiments show that our proposed method can achieve 100% accuracy for 10-class recognition, and 99.68% for a large depression angle. Besides, the proposed method can achieve satisfactory accuracy even with reduced datasets. Experimental results have shown that our proposed method outperform other state-of-the-art ATR methods.

关键词： Training Synthetic aperture radar Feature extraction Radar polarimetry Target recognition Data models Image sequences

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Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

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Frontiers of Earth Science 2017年第1期11卷 11-19页

作者： Menglong YAN Thomas BLASCHKE Hongzhao TANG Chenchao XIAO Xian SUN Daobing ZHANG Kun FU Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Z GIS - Centre for Geoinformatics and Department for Geography and Geology University of Salzburg Salzburg A-5020 Austria Satellite Mapping Application Center State Bureau of Surveying and Mapping Beijing 100048 China China Aero Geophysical Survey and Remote Sensing Center for Land and Resources Beijing 100083 China

Airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

关键词： airborne laser scanning object-based analysis surface complexity information filtering algorithm

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Self-Tuning Asynchronous Filter for Linear Gaussian system and applications

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1054-1061页

作者： Wenjun Lv Yu Kang Yunbo Zhao Department of Automation University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Fire Science Department of Automation and Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei 230027China Key Laboratory of Technology in GeoSpatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China College of Information Engineering Zhejiang University of TechnologyHangzhou 310023China

In this paper, optimal filtering problem for a class of linear Gaussian systems is studied. The system states are updated at a fast uniform sampling rate and the measurements are sampled at a slow uniform sampling rate. The updating rate of system states is several times the sampling rate of measurements and the multiple is constant. To solve the problem,we will propose a self-tuning asynchronous filter whose contributions are twofold. First, the optimal filter at the sampling times when the measurements are available is derived in the linear minimum variance sense. Furthermore, considering the variation of noise statistics, a regulator is introduced to adjust the filtering coefficients adaptively. The case studies of wheeled robot navigation system and air quality evaluation system will show the effectiveness and practicability in engineering.

关键词： Air quality evaluation system linear Gaussian system wheeled robot navigation system

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A Multicast Architecture of SVC Streaming Over OpenFlow Networks

A Multicast Architecture of SVC Streaming Over OpenFlow Netw...

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IEEE Global Communications Conference

作者： Enzhong Yang Yongyi Ran Shuangwu Chen Jian Yang CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

ISBN: (纸本)9781479935130

In video streaming service, multicast mode is a promising way to complement unicast delivery of content, since it deliveries the video content to a broad range of receivers. It is considered as an efficient scheme to reduce redundant traffic in the networks. In this paper, we propose an OpenFlow based architecture for implementing Scalable Video Coding (SVC) multicast streaming. It enables in-network identifying, processing and manipulating the media streams, which makes prompt bitrate adaptation possible in response to network fluctuations. The heterogeneous video quality demand from the heterogeneous device also can be satisfied by customizing the multicast traffic through a centralized OpenFlow controller. We implement a testbed following the proposed architecture in our campus. With OpenFlow, we deploy IP multicast in a new way without Internet Group Management Protocol (IGMP) or any multicast addresses. Experiments implemented on the testbed show that our approach can provide a flexible and controllable video multicast streaming service and improve the usage of bandwidth resource in the condition of guaranteeing multicast receivers' Quality of Experience (QoE).

关键词： IP networks multicast communication telecommunication traffic video coding video streaming IP multicast OpenFlow networks bandwidth resource usage improvement bitrate adaptation centralized OpenFlow controller controllable video multicast streaming service heterogeneous device heterogeneous video quality demand media streams multicast SVC streaming architecture multicast receivers quality-of-experience multicast traffic network fluctuations redundant traffic reduction scalable video coding multicast streaming unicast content delivery Control systems Ports (Computers) Receivers Servers Static VAr compensators Streaming media

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3-D context entropy model for improved practical image compression

arXiv

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arXiv 2020年

作者： Guo, Zongyu Wu, Yaojun Feng, Runsen Zhang, Zhizheng Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthened with residual structures. In short, we make three noteworthy improvements here. First, we propose a 3-D context entropy model which can take advantage of known latent representation in current spatial locations for better entropy estimation. Second, a light-weighted residual structure is adopted for feature learning during entropy estimation. Finally, an effective training strategy is introduced for practical adaptation with different resolutions. Experiment results indicate our image compression method achieves 0.9775 MS-SSIM on CLIC validation set and 0.9809 MS-SSIM on test set. Copyright © 2020, The Authors. All rights reserved.

关键词： Image compression

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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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