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IET International Radar Conference 2013

作者： Hui, Zhang Jun, Hong University of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing Institute of Electronics China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Technology Beijing China Science and Technology on Microwave Imaging Laboratory Beijing China

ISBN: (纸本)9781849196031

Along-Track Interferometric Synthetic Aperture Radar (ATISAR) has the potential of measuring the radial velocity of the slowly moving target. The accuracy of the radial velocity is mainly determined by the accuracy of the interferometric parameters. Sensitivity equations are good ways of analysing the impacts of system parameters for interferometric SAR. Former sensitivity analysis for ATI-SAR has been mainly focused on the case of no squint angle. In this paper, we explain the necessity of analysing the sensitivity equations in the presence of squint angle. Then the expression of the radial velocity in the presence of squint is derived and the sensitivity equations are obtained. Finally, the sensitivity of some interferometric parameters and the impact of squint angles are analysed and simulated for a particular accuracy requirement.

关键词： Sensitivity analysis

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A METHOD OF AIRBORNE INSAR DEM RECONSTRUCTION IN LAYOVER AREAS

A METHOD OF AIRBORNE INSAR DEM RECONSTRUCTION IN LAYOVER ARE...

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IEEE International geoscience and Remote Sensing Symposium

作者： Fangfang LI Bing HAN Xue LIN Donghui HU Chibiao DING Key Laboratory of Geo-Spatial Information Processing and Application System Technology Chinese Academy of Sciences

ISBN: (纸本)9781467311601

The layover phenomenon of SAR imaging arises when different height contributions collapse in the same range-azimuth resolution cell, due to the presence of strong terrain slopes or discontinuities in the scenarios. Because of the phase discontinuities, for single baseline interferometric SAR, it is difficult to recover the accurate unwrapped phase in layover areas by traditional phase unwrapping methods. In this paper, according to the phase characteristic of layover areas, we propose a new method to retrieve unwrapped phase based on local frequency estimate. It can avoid the unwrapping error resulted from the phase jump at the edge of layover areas. As a result, relative accurate DEM of layover areas can be reconstructed, which is beneficial to afterward geocoding in InSAR topographic mapping.

关键词： SAR interferometry Layover Interferometric phase DEM reconstruction Local frequency estimate phase step resolution cell local frequency Synthetic aperture radar discontinuities Phase indium Radar polarimetry geocoding Topographic Mapping Reconstructions PHASE LAG CHARACTERISTIC

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Unambiguous Imaging for Moving Targets in Maritime Scenarios with Dual Receive Channel Mode of GF-3 Satellite 6

Unambiguous Imaging for Moving Targets in Maritime Scenarios...

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

作者： Yang, Junying Qiu, Xiaolan Zhong, Lihua DIng, Chibiao Huang, Lijia Chen, Hao Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences Beijing100190 China Fifth Laboratory Institute of Communication and Tracking Technology Beijing100190 China

ISBN: (纸本)9781728129129

Gaofen-3 (GF-3) is the first Chinese multichannel synthetic aperture radar (SAR) sensor that can operate in the dual receive channel (DRC) mode. Different from the traditional single-channel SAR system, the multichannel SAR system can overcome the inherent limitation to achieve high-resolution and wide-swath (HRWS) at the same time. However, the key challenge it faces is false target suppression. Especially for the moving vessels on the ocean, the existence of false targets will increase false alarm probability and affect the interpretation of SAR images. In this paper, the method of integration of detection, velocity estimation, location, and imaging for moving targets in the HRWS SAR system is proposed as well as applied to get an unambiguous image. The simulation and GF-3 real data experimental results show the validity of the method. © 2019 IEEE.

关键词： Synthetic aperture radar

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Remote Sensing Image Matching and Localization Method Based on the MySQL Multi-Feature Control Point Database 9

Remote Sensing Image Matching and Localization Method Based ...

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9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Zilu, Zhao Feng, Wang Hongjian, You Peifeng, Li Tingtao, Zhang Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350385991

With the increase in the number of remote sensing satellites and imaging modes, the amount of data for acquiring remote sensing images has greatly increased. Effectively and stably performing geometric positioning on remote sensing images is the foundation of remote sensing applications. This paper proposes a remote sensing image matching and positioning method based on a multi-feature control point database in MySQL. Firstly, a feature control point database in MySQL is constructed based on multiple feature methods. Subsequently, the target image is matched from coarse to fine using region features and point features in the feature control point database. Experimental results show that, on three target remote sensing images, the coarse-to-fine matching method based on MySQL multi-feature database can achieve good geometric positioning effects, with a positioning accuracy of around 0.5 pixels. © 2024 IEEE.

关键词： Optical remote sensing

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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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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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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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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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