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IEEE International geoscience and Remote Sensing Symposium

作者： Ling Wan Yuming Xiang Hongjian You Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

This paper proposes an extension version of our previous work MS-CC to achieve optical and SAR images change detection. The proposed method introduces a cooperative multitemporal segmentation, whose merging process considers the heterogeneity of SAR and optical images as parallel information, making sure that the multitemporal information can be fully utilized without interfering with each other. Then, the change detection strategy based on compound classification is carried out on the segmentation results, obtaining the multi-scale change detection maps. Experimental validation is conducted with GoaFen3 and Google Earth data.

关键词： Image segmentation Optical imaging Radar polarimetry Optical sensors Compounds Interference Stacking

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A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOLUTION SAR IMAGE

A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOL...

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IEEE International geoscience and Remote Sensing Symposium

作者： Wenji Xing Xiaolan Qiu Chibiao Ding The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

High-resolution SAR has large transmitting bandwidth and wide synthetic aperture. How to understand and take advantage of the variation characteristics of SAR scattering characteristics with angle and frequency is a topic that worth studying. This article establishes a coherence matrix of sub-band and sub-aperture SAR images, and analyzes its ability to classify scattering mechanism. Experiments are conducted using the TerraSAR-X high-resolution data of different scenarios, and some meaningful results are got, which may provide some support to the analysis and application of high-resolution SAR data.

关键词： Coherence Entropy Azimuth Radar polarimetry Synthetic aperture radar Image resolution

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ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 POLARIMETRIC DATA

ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 P...

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IEEE International geoscience and Remote Sensing Symposium

作者： Songtao Shangguan Xiaolan Qiu Bin Lei The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

With the needs of quality assessment for massive GF-3 polarimetric data, a method based on common distribution targets has been proposed by Sha Jiang. However, it needs manually selection of those woodlands, and cannot be performed automatically. In this paper, an automated GF-3 full-polarization SAR data quality assessment method is conducted using a classic Convolution Neural Network (VGG-16). The network is pre-trained by Radarsat-2 PolSAR data and then trained by selected typical GF-3 scenes. It is supposed to learn the features of the targets, which satisfies the azimuthal symmetry and backscatter reciprocity and fulfills the quality assessment work. Several typical GF-3 strips data are used to test the method. Experiments show that the network can predict the plots of targets from a new scene under the interference of polarimetric distortion and noise. And, the quality assessment results by the network are consistent with the manual assessment results, which shows the effectiveness of the method.

关键词： Quality assessment Distortion Data integrity Strips Manuals Forestry Radar polarimetry

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An Approach for Spaceborne InSAR DEM Inversion Integrated with Stereo-SAR Method

An Approach for Spaceborne InSAR DEM Inversion Integrated wi...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Fangfang Li Yueting Zhang Xiaolan Qiu Key Laboratory of Geo-spatial Information Processing and Application System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has the capability of high precise topographic mapping for large area. However, on the one hand, digital elevation models (DEM) inversion needs at least one ground control points (GCP) to obtain absolute interferometric phase as the unwrapped phase is just a relative value. On the other hand, the baseline value used for DEM inversion also needs to be calibrated using GCPs due to the measure error. In practice, it is difficult to manually deploy GCPs especially in the area of steep topography. At present, with the improvement of orbital measure accuracy and system time accuracy for spaceborne SAR satellite, high precise absolute 3D location information of some stable point scatterers can be obtained by stereo SAR using data from different viewing angles. Therefore, this paper combines stereo SAR with InSAR. These point scatters are used as GCPs to calibrate baseline and estimate absolute phase. As a result, high accurate DEM generation without GCPs can be achieved. The experiment using TerraSAR-X data verifies the effectiveness of this method.

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Secrecy relaying strategy over correlated fading channels using CSI estimation 5

Secrecy relaying strategy over correlated fading channels us...

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5th International Conference on Communication and information processing, ICCIP 2019

作者： Chen, Wang Wang, Mingzhi Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Institute of Electronics Chinese Academy of Sciences No. 19 North 4th Ring Road West Haidian District Beijing100191 China

ISBN: (纸本)9781450372589

Cooperative relaying is considered as an effective method to improve the secrecy performance of wireless communications. However, the existing relay selection strategies do not consider the channel correlations between the main and eavesdropping links which limits the secrecy performance. In this paper, the authors explore how to select relay under correlated fading channels in a multiple decode-and-forward (DF) relay network. To this end, the authors adopt the minimum mean squared error (MMSE) method to estimate the channel state information (CSI) of relay-eavesdropper link based on the channel correlation and then propose the single-relay selection (SRS) strategy. Simulation results show that the proposed SRS strategy outperforms other SRS strategies significantly. To further improve the secrecy performance of the DF system, we propose a novel multiple-relay selection (MRS) method for correlated channels taking advantage of estimating the relay-eavesdropper channel. Results show that our MRS strategy performs better than its SRS version and other MRS strategies. We also find that the our MRS strategy gets more performance gain than other strategies with the number of relays increases indicating the effectiveness of estimating the eavesdropping channel in secure relaying. © 2019 Association for Computing Machinery.

关键词： Channel state information

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InSAR DEM Reconstruction Based on Backprojection Algorithm in Two Converse Flights 6

InSAR DEM Reconstruction Based on Backprojection Algorithm i...

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

作者： Hu, Xiaoning Xiang, Maosheng Wang, Bingnan Fu, Xikai University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China National Key Laboratory of Science and Technology on Microwave Imaging Institute of Electronics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

Interferometric synthetic aperture radar (InSAR) can be used to extract digital elevation model (DEM) with high accuracy. However, the side looking geometry of synthetic aperture radar (SAR) may cause geometric distortions such as shadow and layover in the mountainous terrain, which will reduce the quality of generated DEM. Fusion of two or more different aspects of InSAR data can deal with this problem. We propose an InSAR DEM reconstruction method based on backprojection (BP) algorithm in two converse flights. This method utilizes the feature of BP algorithm that geocoding has been realized in imaging process to simplify the fusion process of multi-aspect InSAR data. In addition, an iterative DEM extraction method is introduced to improve DEM accuracy. Experimental results verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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

Unambiguous Imaging for Moving Targets in Maritime Scenarios...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

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

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

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.

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An accurate SAR imaging method based on generalized minimax concave penalty 12

An accurate SAR imaging method based on generalized minimax ...

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Wei, Zhonghao Zhang, Bingchen Han, Bing Xu, Zhilin Hong, Wen Wu, YiRong University of Chinese Academy of Science and Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences China Laboratory of Technology in Geo-spatial Information Processing and Application Systems Institute of Electronics Chinese Academy of Sciences China Institute of Electronics Chinese Academy of Sciences China

ISBN: (纸本)9783800746361

Sparse signal processing has been applied in synthetic aperture radar (SAR) imaging successfully. As a typical sparse reconstruction model, L1 regularization often underestimates the intensities of the targets. The estimated radar cross section (RCS) is related to the pixel intensity. The underestimation will cause the errors in RCS estimations. In this paper, we present a SAR imaging method based on generalized minimax convex (GMC) penalty, which can avoid the pixel intensity underestimation. The performance of the proposed method is verified using simulations and real data. © VDE VERLAG GMBH Â Berlin Â Offenbach.

关键词： Radar cross section

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Classification of large-scale high-resolution SAR images with deep transfer learning

arXiv

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arXiv 2020年

作者： Huang, Zhongling Dumitru, Corneliu Octavian Pan, Zongxu Lei, Bin Datcu, Mihai Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Huairou District Beijing101408 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Wessling82234 Germany

The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with expertise, changing data characteristics due to varying imaging parameters or regional target area differences, and complex scattering mechanisms being different from optical imaging. Given a large-scale SAR land cover dataset collected from TerraSAR-X images with a hierarchical three-level annotation of 150 categories and comprising more than 100,000 patches, three main challenges in automatically interpreting SAR images of highly imbalanced classes, geographic diversity, and label noise are addressed. In this letter, a deep transfer learning method is proposed based on a similarly annotated optical land cover dataset (NWPU-RESISC45). Besides, a top-2 smooth loss function with cost-sensitive parameters was introduced to tackle the label noise and imbalanced classes' problems. The proposed method shows high efficiency in transferring information from a similarly annotated remote sensing dataset, a robust performance on highly imbalanced classes, and is alleviating the over-fitting problem caused by label noise. What's more, the learned deep model has a good generalization for other SAR-specific tasks, such as MSTAR target recognition with a state-of-the-art classification accuracy of 99.46%. Copyright © 2020, The Authors. All rights reserved.

关键词： Synthetic aperture radar

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HDEC-TFA: An unsupervised learning approach for discovering physical scattering properties of single-polarized SAR image

TechRxiv

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TechRxiv 2020年

作者： Huang, Zhongling Datcu, Mihai Pan, Zongxu Qiu, Xiaolan Lei, Bin Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Huairou District Beijing101408 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Wessling82234 Germany

Knowing the physical properties and scattering mechanisms contributes to Synthetic Aperture Radar (SAR) image interpretation. For single-polarized SAR data, however, it is difficult to extract the physical scattering mechanisms due to lack of polarimetric information. Time-frequency analysis (TFA) on complex-valued SAR image provides extra information in frequency perspective beyond the’image’ domain. Based on TFA theory, we propose to generate the sub-band scattering pattern for every object in complex-valued SAR image as the physical property representation, which reveals backscattering variations along slant-range and azimuth directions. In order to discover the inherent patterns and generate a scattering classification map from single-polarized SAR image, an unsupervised hierarchical deep embedding clustering algorithm based on time-frequency analysis (HDEC-TFA) is proposed to learn the embedded features and cluster centers simultaneously and hierarchically. The polarimetric analysis result for quad-pol SAR images is applied as reference data of physical scattering mechanisms. In order to compare the scattering classification map obtained from single-polarized SAR data with the physical scattering mechanism result from full-polarized SAR, and to explore the relationship and similarity between them in a quantitative way, an information theory based evaluation method is proposed. We take Gaofen-3 quad-polarized SAR data for experiments and the results and discussions demonstrate that the proposed method is able to learn valuable scattering properties from single-polarization complex-valued SAR data, and to extract some specific targets as well as polarimetric analysis. At last, we give a promising prospect to future applications. © 2020, CC BY.

关键词： Synthetic aperture radar

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