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IET International Radar Conference 2020, IET IRC 2020

作者： Lv, Yini Zhong, Lihua Yang, Junying Qiu, Xiaolan Yuan, XinZhe Han, Bing Ding, Chibiao Aerospace Information Research Institute Chinese Academic of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China National Satellite Ocean Application of Service Beijing China

ISBN: (纸本)9781839535635

This paper proposes a method for the ship target azimuth offset correction on the Synthetic Aperture Radar (SAR) image using Automatic Identification System (AIS) data. Traditional AIS and SAR image ship matching usually use AIS position, size, and other information. This paper uses a continuous position sequence around the SAR image acquisition time, that is, the complete trajectory, to calculate the slant range between the ship and the space-borne SAR platform. By deriving the slant range, the radial velocity can be obtained. According to the radial velocity, the azimuth offset of the moving ship is estimated to correct the ship's position on the SAR image. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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A Differentiable Framework for Image-Based SAR Target Reconstruction with 3D Gaussian Splatting

A Differentiable Framework for Image-Based SAR Target Recons...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Zinan Liu Shengren Niu Xiaolan Qiu Lingxiao Peng Lihua Zhong Chibiao Ding The National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Aerospace Information Research Institute Chinese Academy of Sciences Suzhou China Key Laboratory of Technology in Geospatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Image-based synthetic aperture radar (SAR) target three-dimensional (3D) reconstruction is an important application for extracting target information from high-resolution two-dimensional (2D) SAR images. However, due to the complex mechanism of SAR imaging, developing a data-driven, fully automated 3D reconstruction framework with explicit physical constraints is very difficult. Thus, this paper proposes a differentiable framework for image-based SAR target reconstruction with 3D Gaussian Splatting, which can automatically realize the 3D target reconstruction from multi-view SAR images. Specifically, the proposed differentiable framework accumulates and generates simulated SAR images according to the SAR imaging geometry and projection during the forward simulation stage. By calculating the loss between the simulated and ground truth SAR images and backpropagating, the spatial positions of the 3D Gaussians are continuously adjusted until convergence, generating the 3D point cloud model of the target. The experiment is conducted on the constructed T72 SAR image dataset and the reconstruction results demonstrate the effectiveness of the proposed framework.

关键词： Point cloud compression Geometry Solid modeling Three-dimensional displays Two-dimensional displays Data processing Radar polarimetry Robustness Image reconstruction Synthetic aperture radar

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A NOVEL APPROACH TO PHASE ERROR ESTIMATION IN MULTI-CHANNEL SCANSAR

A NOVEL APPROACH TO PHASE ERROR ESTIMATION IN MULTI-CHANNEL ...

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IET International Radar Conference 2023, IRC 2023

作者： Lv, Yini Zhong, Lihua Shang, Mingyang Qiu, Xiaolan Ding, Chibiao Aerospace Information Research Institute Chinese Academic of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781839539954

The phase error between channels in azimuth multi-channel (AMC) synthetic aperture radar (SAR) system can deteriorate the reconstruction performance, leading to azimuth ambiguity in the final image. Therefore, phase error estimation is an essential step in AMC SAR imaging. However, due to the special beam scanning of AMC scanned-beam SAR (ScanSAR), the Doppler spectrum of the point target is incomplete and asymmetric, which makes the traditional phase error estimation methods unsuitable for ScanSAR. Taking the Doppler spectrum characteristics into account, a new method of multi-channel ScanSAR phase error estimation is proposed. The proposed method divides the Doppler centroid (DC) of the strong scattering point target into baseband DC and ambiguity DC. The spatial cross-correlation coefficient (SCCC) method is adopted to estimate the baseband DC. Then, the frequency cross-correlation coefficient (FCCC) method is proposed to estimate the DC ambiguity number. After estimating the precise DC, the frequency correlation method (FCM) is improved to estimate the phase error. Finally, the validation of the proposed method is demonstrated with the simulation data and GF-3 dual channel data. © The Institution of Engineering & technology 2023.

关键词： Synthetic aperture radar

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Multi-Channel Spaceborne SAR Imaging Method for Maritime Scenarios

Multi-Channel Spaceborne SAR Imaging Method for Maritime Sce...

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Sensor Array and Multichannel Signal processing Workshop

作者： Xiaolan Qiu Junying Yang Mingyang Shang Lihua Zhong Chibiao Ding Key Laboratory of Technology in GeoSpatial Information Processing and Application Systems Aerospace Information Research Institute Chinese Academy of Sciences Beijing China National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The spaceborne SAR is required to fulfill the increasing demands for improved spatial resolution and wider swath coverage in recent years. The azimuth multi-channel SAR system is a typical technique adopted for realizing high-resolution and wide-swath (HRWS) simultaneously. The flexibility of this system also provides favorable conditions for moving target detection. Aiming at the problems of moving target detection, velocity estimation, and imaging of SAR maritime scenes in the spaceborne multi-channel system, this paper proposes a set of processes based on coarse imaging, detection, velocity estimation and refocusing. The experimental results of the simulation verify the effectiveness of the method.

关键词： Azimuth Conferences Imaging Estimation Object detection Radar polarimetry Doppler effect

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AN ANISOTROPIC SCATTERING ANALYSIS METHOD BASED ON LIKELIHOOD RATIO USING CIRCULAR SAR DATA

AN ANISOTROPIC SCATTERING ANALYSIS METHOD BASED ON LIKELIHOO...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Fei Teng Wen Hong Yun Lin Bing Han Yanping Wang Wenjie Shen Shanshan Feng Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China North China University of Technology Beijing China

The scattering of an anisotropic target is aspect dependent. Circular SAR (CSAR) can observe the scattering behavior in different aspect angles. In this paper, we propose an anisotropy scattering analysis method based on the likelihood ratio using CSAR data. CSAR data is used to provide sub-aperture images in different aspect angles. The likelihood ratio is defined as the ratio of the conditional probability under two hypotheses, anisotropic and isotropic. Anisotropic and isotropic scatterings can be discriminated by the value of the likelihood ratio. The scattering direction of the anisotropic scattering can be obtained by using our method too. We use a C-band CSAR data, which is acquired by the Institute of Electronics, Chinese Academy of Sciences (IECAS) to validate our method.

关键词： Apertures Image color analysis Radar polarimetry Trajectory Optical imaging Optical scattering

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Effects of residual motion compensation errors on the performance of airborne along-track interferometric SAR

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Frontiers of information technology & Electronic Engineering 2016年第10期17卷 1095-1105页

作者： Hui ZHANG Jun HONG Xiao-lan QIU Ji-chuan LI Fang-fang LI Feng MING Institute of Electronics Chinese Academy of Sciences Beoing 100190 China University of the Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Beijing 100190 China Science and Technology on Millimeter-Wave Laboratory Beijing 100854 China

Two approximations, center-beam approximation and reference digital elevation model （DEM） approximation, are used in synthetic aperture radar （SAR） motion compensation procedures. They usually introduce residual motion compensation errors for airborne single-antenna SAR imaging and SAR interferometry. In this paper, we investigate the effects of residual uncompensated motion errors, which are caused by the above two approximations, on the performance of airborne along-track interferometric SAR （ATI-SAR）. The residual uncompensated errors caused by center-beam approximation in the absence and in the presence of elevation errors are derived, respectively. Airborne simulation parameters are used to verify the correctness of the analysis and to show the impacts of residual uncompensated errors on the interferometric phase errors for ATI-SAR. It is shown that the interferometric phase errors caused by the center-beam approximation with an accurate DEM could be neglected, while the interferometric phase errors caused by the center-beam approximation with an inaccurate DEM cannot be neglected when the elevation errors exceed a threshold. This research provides theoretical bases for the error source analysis and signal processing of airborne ATI-SAR.

关键词： Synthetic aperture radar (SAR) Along-track interferometric Motion compensation Residual error Interferometric phase

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Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation

arXiv

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arXiv 2020年

作者： Li, Ziqiang Tao, Rentuo Niu, Hongjing Li, Bin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems University of Science and Technology of China Anhui China

Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner process of GANs is far from been understood. To get deeper insight of the intrinsic mechanism of GANs, in this paper, a method for interpreting the latent space of GANs by analyzing the correlation between latent variables and the corresponding semantic contents in generated images is proposed. Unlike previous methods that focus on dissecting models via feature visualization, the emphasis of this work is put on the variables in latent space, i.e. how the latent variables affect the quantitative analysis of generated results. Given a pretrained GAN model with weights fixed, the latent variables are intervened to analyze their effect on the semantic content in generated images. A set of controlling latent variables can be derived for specific content generation, and the controllable semantic content manipulation be achieved. The proposed method is testified on the datasets Fashion-MNIST and UT Zappos50K, experiment results show its effectiveness. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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MULTICHANNEL SLIDING SPOTLIGHT SAR IMAGING BASED ON SPARSE SIGNAL processing

MULTICHANNEL SLIDING SPOTLIGHT SAR IMAGING BASED ON SPARSE S...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Zhilin Xu Zhonghao Wei Chenyang Wu Bingchen Zhang Institute of Electronics Chinese Academy of Sciences Geospatial Information Processing and Application System Key Laboratory of Technology University of Chinese Academy of Sciences Beijing China

Multi-channel sliding spotlight SAR can achieve high-resolution and wide-swath imaging. The sparse reconstruction algorithm can improve the quality of imaging. By applying the sparse reconstruction algorithm to multichannel sliding spotlight SAR imaging, azimuth ambiguities, noise and clutter can be suppressed effectively. In this paper, l_1 regularization based multi-channel sliding spotlight SAR imaging method is proposed. The proposed method combines the DPCA imaging operators with the l_1 regularization scheme to solve the nonuniform sampling and azimuth ambiguities problem. The proposed method can suppress azimuth ambiguities more effectively than the reconstruction filter algorithm based DPCA technology in the case of a lower PRF. The experiment results verify the effectiveness of the proposed method.

关键词： Multi-channel Sliding spotlight SAR DPCA L_1 regularization

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Multi-Angular SAR Statistical Properties Analysis and Man-Made Target Detection

Multi-Angular SAR Statistical Properties Analysis and Man-Ma...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fei Teng Yun Lin Yanping Wang Wenjie Shen Shanshan Feng Wen Hong Key Laboratory of Technology in Geospatial Information Processing and Application System Chinese Academy of Sciences Beijing China School of Electronic Information Engineering North China University of Technology Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

In conventional synthetic aperture radar (SAR) working mode, targets are assumed isotropic due to the limited aperture length. However, most of man-made targets are anisotropic. Therefore, the anisotropic scattering can help us do man-made target detection. Circular SAR (CSAR) [1] is a new SAR working mode and it can obtain the anisotropic scattering of the target by 360° observation. In this paper, the multi-angular statistical properties of targets are analyzed. The probability density functions (PDF) of the anisotropic target are various under different aspect viewing angles, while the PDFs of the isotropic target are basically stable. Then a man-made target detection method is proposed based on the multi-angular statistical property. Likelihood ratio test [2] is used to judge whether the statistical property of scattering is anisotropic or isotropic. Then anisotropic scatterings, which represent the man-made targets, can be discriminated from isotropic scatterings by thresholding. An X-band chamber circular SAR data and a C-band airborne circular SAR data are used to illustrated our idea.

关键词： Scattering Radar polarimetry Synthetic aperture radar Object detection Apertures Fitting Buildings

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A FEATURE ENHANCEMENT METHOD BASED ON THE SUB-APERTURE DECOMPOSITION FOR ROTATING FRAME SHIP DETECTION IN SAR IMAGES

A FEATURE ENHANCEMENT METHOD BASED ON THE SUB-APERTURE DECOM...

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2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

作者： Lei, Songlin Qiu, Xiaolan Ding, Chibiao Lei, Shujie National Key Laboratory of Microwave Imaging Technology Beijing100190 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Shanghai Radio Equipment Research Institute Shanghai201100 China

ISBN: (纸本)9781665403696

Deep learning algorithms are widely used in SAR target detection. At present, most detection methods based on neural networks treat SAR images as optical images for processing, and do not fully exploit the characteristics of SAR images. In this paper, a method for feature enhancement using sub-aperture decomposition is proposed. Considering the advantages of the rotate box in eliminating interference, we conducted experiments on the rotating frame detection network Rotate RetinaNet using the Complex SAR images Rotation Ship Detection Dataset (CSRSDD). Compared with the base method, AP improves by 2.4% without bells and whistles. The results confirm the effectiveness of the proposed method. © 2021 IEEE

关键词： Neural networks Optical computing Object detection Optical fiber networks Optical detectors Optical imaging Radar polarimetry

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