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检索条件"机构=the Key Laboratory of Technology in Geo-Spatial information Processing and Application System"

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L-hypersurface Based Parameters Selection for Sparse SAR Imaging via Composite Regularization

L-hypersurface Based Parameters Selection for Sparse SAR Ima...

引用

2022 International Conference on Radar systems, RADAR 2022

作者： Fan, Yizhe Xu, Zhongqiu Zhou, Guoru Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences China Key Laboratory of Technology in Geo-spatial Information Processing and Application System School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781839537776

Composite regularization models are widely used in sparse signal processing, making multiple regularization parameters selection a significant problem to be solved. Variety kinds of composite regularization models are used in SAR imaging, including L1 and TV penalty, L1 and L2,1 penalty, etc. In this article, a new adaptive multiple regularization parameters selection method named L-hypersurface is proposed. The effectiveness of the proposed method is verified by experiments. Simulation experiments indicate that the selected optimal regularization parameters have satisfied reconstruction results, both visually and numerically. Furthermore, experiments on Gaofen-3 SAR satellite data are also exploited to show the performance of the proposed method. © IET Conference Proceedings. All rights reserved.

关键词： Synthetic aperture radar

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Parameter prediction method of SAR target simulation based on convolutional neural networks 12

Parameter prediction method of SAR target simulation based o...

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12th European Conference on Synthetic Aperture Radar, EUSAR 2018

作者： Shengren, Niu Xiaolan, Qiu Lingxiao, Peng Bin, Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute ofElectronics Chinese Academy of Sciences University of Chinese Academy of Sciences China Suzhou Institute Institute of Electronics Chinese Academy of Sciences China

ISBN: (纸本)9783800746361

SAR image simulation plays a useful role in SAR target interpretation and recognition. The current SAR target simulation methods require high precision of models and simulation parameters, and are only forward processes which lack the feedback adjustment of real image. In this paper, a method of predicting simulation parameters from real images is proposed, which is based on convolutional neural networks(CNN). The architecture and the loss function of the CNN are modified to obtain better performance of the parameter inversion. From the simulation results, the predicted parameters improve the similarity between the simulation images and the real images. © VDE VERLAG GMBH Â Berlin Â Offenbach.

关键词： Synthetic aperture radar

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Transform-invariant convolutional neural networks for image classification and search 24

Transform-invariant convolutional neural networks for image ...

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24th ACM Multimedia Conference, MM 2016

作者： Shen, Xu Tian, Xinmei He, Anfeng Sun, Shaoyan Tao, Dacheng CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

ISBN: (纸本)9781450336031

Convolutional neural networks (CNNs) have achieved stateof-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of images. Intuitively, with sufficient layers and parameters, hierarchical combinations of convolution (matrix multiplication and nonlinear activation) and pooling operations should be able to learn a robust mapping from transformed input images to transform-invariant representations. In this paper, we propose randomly transforming (rotation, scale, and translation) feature maps of CNNs during the training stage. This prevents complex dependencies of specific rotation, scale, and translation levels of training images in CNN models. Rather, each convolutional kernel learns to detect a feature that is generally helpful for producing the transforminvariant answer given the combinatorially large variety of transform levels of its input feature maps. In this way, we do not require any extra training supervision or modification to the optimization process and training images. We show that random transformation provides significant improvements of CNNs on many benchmark tasks, including small-scale image recognition, large-scale image recognition, and image retrieval. © 2016 ACM.

关键词： Mathematical transformations

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An automatic interpretation approach for high resolution urban remote sensing image using objects-based boosting model

An automatic interpretation approach for high resolution urb...

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2009 Joint Urban Remote Sensing Event

作者： Xian, Sun Hui, Long Hongqi, Wang Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424434619

For the purpose of interpreting urban remote sensing images more effectively and comprehensively, this paper proposes a new automatic approach using objects-based boosting model. The approach associates segmentation with recognition by constructing a hierarchical objects network at first, which effectively improves the problem of detecting targets with a modifiable sliding window existed in other methods. Then the probabilistic learning integrating multiple features including color, texture, shape and location is performed to train a multi-class classifier, and label all of the objects according to their classification values. The approach also applies spatial smoothing which incorporates contextual information to eliminate the adverse effects caused by background disturbance, occlusion and so on. After vectorization procedure, final result is given. Experiments demonstrate that proposed approach achieve high exactness and robustness in interpreting manifold urban remote sensing images. ©2009 IEEE.

关键词： Remote sensing

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The development and performance of the prototype coded ARC

The development and performance of the prototype coded ARC

引用

2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Liang, Li Caiyun, Wang Yongtao, Zhu Jun, Hong Key Laboratory of Spatial Information Processing Application System Technology Chinese Academy of Sciences Beijing China Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424427314

The development and performance of a prototype coded Active Radar Calibration (ARC) in S-band,which is used as a ground calibration reference standard for Synthetic Aperture Radar(SAR), are described. The coded ARC uses phase shifting and delay techniques which affect the SAR signal in azimuth and *** ratio of the ARC signal to the background signal is improved. An internal gain stabilization subsystem, which ensures the stability of the complete signal path and Effective Isotropic Radiated Power(ERIP),is included in the prototype coded ARC. An experiment was made in microwave chamber to prove the precision of the coded ARC's Radar Cross Section(RCS).The precision concluded from the result of the experiment is

关键词： Calibration

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Sensitivity analysis of along-track interferometric synthetic aperture radar (ATI-SAR) in the presence of squint

Sensitivity analysis of along-track interferometric syntheti...

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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 ...

引用

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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