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IET International Radar Conference 2023, IRC 2023

作者： Wang, Muhan Gao, Silin Zhang, Zhe Qiu, Xiaolan Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781839539954

Synthetic aperture radar (SAR) tomography (TomoSAR) has garnered significant attention due to its capability for three-dimensional reconstruction. Compressed sensing (CS) methods are widely employed to address the TomoSAR inversion challenge. Nevertheless, practical applications reveal phase errors among different channels, resulting in defocusing and blurring when relying solely on CS for 3D reconstruction. Current state-of-the-art autofocus techniques suffer from prohibitive computational complexity, limiting their applicability to large-scale 3D imaging. In pursuit of efficient TomoSAR 3-D autofocusing, we proposed ASAMP-Net, an innovative deep unfolding network. Operating within a two-step framework, each layer comprises two stages: phase error estimation and iterative scattering coefficient reconstruction using the sparse adaptive matching pursuit (SAMP) algorithm. Additionally, phase error estimation is obtained through mathematical derivation, while challenges associated with fixed sparsity and limited efficiency in conventional methods are mitigated through deep learning techniques. Simulation experiments and real data validation affirm the effectiveness and superiority of the proposed method. © The Institution of Engineering & technology 2023.

关键词： Radar imaging

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GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC NORM MINIMIZATION WITH EFFICIENCY

GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC...

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2022 International Conference on Radar systems, RADAR 2022

作者： Gao, Silin Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China

ISBN: (纸本)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) enables the reconstruction and three-dimensional (3D) localization of targets based on multiple two-dimensional (2D) observations of the same scene. The resolving along the elevation direction can be treated as a line spectrum estimation problem. However, traditional super-resolution spectrum estimation algorithms require multiple snapshots and uncorrelated targets. Meanwhile, as the most popular TomoSAR imaging method in modern years, compressed sensing (CS) based methods suffer from the gridding mismatch effect which markedly degrades the imaging performance. As a gridless CS approach, atomic norm minimization can avoid the gridding effect but requires enormous computing resources. Addressing the above issues, this paper proposes an improved fast ANM algorithm to TomoSAR elevation focusing by introducing the IVDST-ANM algorithm, which reduces the huge computational complexity of the conventional time-consuming semi-positive definite programming (SDP) by the iterative Vandermonde decomposition and shrinkage-thresholding (IVDST) approach, and retains the benefits of ANM in terms of gridless imaging and single snapshot recovery. We conducted experiments using simulated data to evaluate the performance of the proposed method, and reconstruction results of an urban area from the SARMV3D-Imaging 1.0 dataset are also presented. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Compressed sensing

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Controllability of Indu-Bala product networks

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Neural Networks 2025年 190卷

作者： Qiang Zhang Junjie Huang Bo Liu Housheng Su Alatancang Chen School of Mathematical Sciences Inner Mongolia University Hohhot 010021 China School of Information Engineering Minzu University of China Beijing 100081 China National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China School of Mathematical Sciences the Ministry of Education Key Laboratory for Infinite-dimensional Hamiltonian System and Its Algorithm Application Inner Mongolia Normal University Hohhot 010022 China

A composite network formed by factor networks is a new type of complex network model that can describe different types of agents and multiple complicated relationships in complex systems. “Indu-Bala product” of graphs is a new graph operation with symmetry properties and good mathematical expression, which enables one to construct many pairs of respective co-spectral graphs. This work studies the controllability of a composite network formed by factor networks via Indu-Bala product based on Laplacian dynamics. The eigenvalues and eigenvectors of Indu-Bala product networks (IBPNs) can be represented by factors’ eigenvalues and eigenvectors, which can reduce the computational complexity and analytical burden. Based on the PBH test, sufficient and necessary algebraic criterions for controllability of IBPNs are established, which reveal the controllability relationship between entire network and its factors. This work will help one to construct, understand and improve the composite complex network models, and gain insight into the synergistic mechanisms of the networks.

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An Azimuth Resample Method For Bistatic SAR Motion Compensation

An Azimuth Resample Method For Bistatic SAR Motion Compensat...

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8th European Conference on Synthetic Aperture Radar

作者： Xiaolan Qiu Bin Han Dadi Meng Donghui Hu Chibiao Ding Key Laboratory of Technology in Geo-spatial Information Processing and Application System IECAS China Institute of Electronics Chinese Academy of Sciences (IECAS) China

Motion compensation is an indispensable step for generating a high quality image in the airborne SAR system. In bistatic SAR, there are two separate platforms and their velocities cannot keep same all the time. So the echoes are transmitted and received at uniform positions, respectively, which deteriorate the imaging results. In this paper, an azimuth resample method for compensating the velocity variance along the flying direction is promoted, and the difference of azimuth resample between monostatic SAR and bistatic SAR is pointed out. Finally, simulated results show the validity of the method.

关键词： Yttrium Transmitters

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A Hybrid and Explainable Deep Learning Framework for SAR Images

A Hybrid and Explainable Deep Learning Framework for SAR Ima...

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IEEE International Symposium on geoscience and Remote Sensing (IGARSS)

作者： Zhongling Huang Mihai Datcu Zongxu Pan Bin Lei Key Laboratory of Technology in Geo-spatial Information Processing and Application System CAS Remote Sensing Technology Institute (IMF) German Aerospace Center (DLR)

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Deep learning based patch-wise Synthetic Aperture Radar (SAR) image classification usually requires a large number of labeled data for training. Aiming at understanding SAR images with very limited annotation and taking full advantage of complex-valued SAR data, this paper proposes a general and practical framework for quad-, dual-, and single-polarized SAR data. In this framework, two important elements are taken into consideration: image representation and physical scattering properties. Firstly, a convolutional neural network is applied for SAR image representation. Based on time-frequency analysis and polarimetric decomposition, the scattering labels are extracted from complex SAR data with unsupervised deep learning. Then, a bag of scattering topics for a patch is obtained via topic modeling. By assuming that the generated scattering topics can be regarded as the abstract attributes of SAR images, we propose a soft constraint between scattering topics and image representations to refine the network. Finally, a classifier for land cover and land use semantic labels can be learned with only a few annotated samples. The framework is hybrid for the combination of deep neural network and explainable approaches. Experiments are conducted on Gaofen-3 complex SAR data and the results demonstrate the effectiveness of our proposed framework.

关键词： Deep learning Training Annotations Scattering Image representation Radar polarimetry Synthetic aperture radar

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An advanced 2-D spectrum for high-resolution and MEO spaceborne SAR

An advanced 2-D spectrum for high-resolution and MEO spacebo...

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

作者： Huang, Lijia Qiu, Xiaolan Hu, Donghui Ding, Chibiao Key Laboratory of Spatial Information Processing and Application System Technology China Institute of Electronics Chinese Academy of Sciences 19 Beisihuanxi Road Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)9781424427314

In this paper, an advanced range equation is presented for high-resolution and medium-earth-orbit (MEO) synthetic aperture radar (SAR). Besides an additional linear component, this new equation has a similar formalism to conventional hyperbolic range equation (CHRE), so is called the advanced hyperbolic range equation (AHRE). Incorporating with this additional linear coefficient and the other two parameters, the cubic Taylor series expansion of AHRE has exactly the same value as which of the actual range history. Furthermore, a two-dimensional (2-D) spectrum based on AHRE is derived, which is useful for developing efficient SAR algorithms. Simulations validate AHRE and show its advantages in high-resolution and MEO spaceborne SAR cases. ©2009 IEEE.

关键词： Synthetic aperture radar

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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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Evolution of AVS video coding standards: twenty years of innovation and development

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Science China(information Sciences) 2022年第9期65卷 50-73页

作者： Siwei MA Li ZHANG Shiqi WANG Chuanmin JIA Shanshe WANG Tiejun HUANG Feng WU Wen GAO Institute of Digital Media School of Computer Science Peking University Bytedance Inc. Department of Computer Science City University of Hong Kong CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China

Ever since the founding of the Audio and Video Coding Standard(AVS) Workgroup of China in 2002, it has been dedicated to advancing and innovating the digital audio-video industry with highly efficient and economical encoding/decoding technologies. Three representative generations of video coding standards have been finalized and published, consistently improving the coding performance in the past two *** series of AVS standards establish solid foundations for ubiquitous video applications in the areas including acquisition, coding, production, delivery, integrated system, public service, general screen content, and mixed reality media. Along with the standardization process, an extensive amount of studies have been carried out on efficiency-aware designation, algorithm optimization, and hardware implementation of these innovative video coding techniques. This paper explains how those developed techniques provide a lasting impact on the video coding community, extensively, technologically, and systematically. In particular, we provide a comprehensive survey of the three generations of the standards, and timely and in-depth summarize the efforts of the AVS video coding standards in the twenty years. The rate-distortion performance comparisons,in particular in terms of the 8K ultra-high-definition(UHD) contents, reflect the elegant design of the state-of-the-art AVS3 standards. We have also elaborated on a variety of well-established and promising applications, including commercial level real-time 8K encoder, high-frame-rate decoder chip for cell phone,and live streaming solution for sports. In addition, the China Central Television(CCTV) of China Media Group(CMG), the state television of China, has officially launched the first 8K broadcasting channel(CCTV-8K) since 2021 using AVS3. Given the significant success realized by the AVS standards, it is envisioned that a new era of 8K UHD video is arriving.

关键词： video coding AVS standards video applications intelligent coding

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Quantum-behaved PSO-based Lyapunov control of closed quantum systems

Quantum-behaved PSO-based Lyapunov control of closed quantum...

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第40届中国控制会议

作者： Song Liu Sen Kuang Department of Automation University of Science and Technology of China CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China

A Lyapunov-based control scheme is presented to drive closed quantum systems into any target eigenstate with as high population as possible by the quantum-behaved particle swarm optimization（PSO） algorithm. Based on a Lyapunov function with a Hermitian operator to be constructed, a control law with the unknown parameters contained in the Hermitian operator is designed. To achieve high-population state transfer to the target state, we first initialize those unknown parameters by choosing a path to the target state in its energy-level connectivity graph and setting their values along the path. Then, a set of optimal parameters is found by the quantum-behaved PSO algorithm. Finally, numerical simulation experiments are performed on a five-level quantum system and a four-qubit system to demonstrate the effectiveness of the control scheme in this paper.

关键词： Quantum systems Lyapunov control quantum-behaved PSO algorithm energy-level connectivity graph high-population transfer

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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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