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ISAR imaging based on improved phase retrieval algorithm

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Journal of Systems engineering and Electronics 2018年第2期29卷 278-285页

作者： SHI Hongyin XIA Saixue TIAN Ye school of information Science and engineering Yanshan University

Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.

关键词： inverse synthetic aperture radar(ISAR) maneuvering target autofocus imaging phase retrieval oversampling smoothness(OSS)

Multi-scale UDCT dictionary learning based highly undersampled MR image reconstruction using patch-based constraint splitting augmented Lagrangian shrinkage algorithm

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Frontiers of information Technology & Electronic engineering 2015年第12期16卷 1069-1087页

作者： Min YUAN Bing-xin YANG Yi-de MA Jiu-wen ZHANG Fu-xiang LU Tong-feng ZHANG school of information Science & engineering Lanzhou University

Recently, dictionary learning(DL) based methods have been introduced to compressed sensing magnetic resonance imaging(CS-MRI), which outperforms pre-defined analytic sparse priors. However, single-scale trained dictionary directly from image patches is incapable of representing image features from multi-scale, multi-directional perspective, which influences the reconstruction performance. In this paper, incorporating the superior multi-scale properties of uniform discrete curvelet transform(UDCT) with the data matching adaptability of trained dictionaries, we propose a flexible sparsity framework to allow sparser representation and prominent hierarchical essential features capture for magnetic resonance(MR) images. Multi-scale decomposition is implemented by using UDCT due to its prominent properties of lower redundancy ratio, hierarchical data structure, and ease of implementation. Each sub-dictionary of different sub-bands is trained independently to form the multi-scale dictionaries. Corresponding to this brand-new sparsity model, we modify the constraint splitting augmented Lagrangian shrinkage algorithm(C-SALSA) as patch-based C-SALSA(PB C-SALSA) to solve the constraint optimization problem of regularized image reconstruction. Experimental results demonstrate that the trained sub-dictionaries at different scales, enforcing sparsity at multiple scales, can then be efficiently used for MRI reconstruction to obtain satisfactory results with further reduced undersampling rate. Multi-scale UDCT dictionaries potentially outperform both single-scale trained dictionaries and multi-scale analytic transforms. Our proposed sparsity model achieves sparser representation for reconstructed data, which results in fast convergence of reconstruction exploiting PB C-SALSA. Simulation results demonstrate that the proposed method outperforms conventional CS-MRI methods in maintaining intrinsic properties, eliminating aliasing, reducing unexpected artifacts, and removing noise. It

关键词： Compressed sensing(CS) Magnetic resonance imaging(MRI) Uniform discrete curvelet transform(UDCT) Multi-scale dictionary learning(MSDL) Patch-based constraint splitting augmented Lagrangian shrinkage algorithm(PB C-SALSA)

Route Guardian: Constructing Secure Routing Paths in Software-Defined Networking

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Tsinghua Science and Technology 2017年第4期22卷 400-412页

作者： Mengmeng Wang Jianwei Liu Jian Mao Haosu Cheng Jie Chen Chan Qi school of Electronic and information engineering Beihang University

Software-Defined Networking（SDN） decouples the control plane and the data plane in network switches and routers, which enables the rapid innovation and optimization of routing and switching configurations. However,traditional routing mechanisms in SDN, based on the Dijkstra shortest path, do not take the capacity of nodes into account, which may lead to network congestion. Moreover, security resource utilization in SDN is inefficient and is not addressed by existing routing algorithms. In this paper, we propose Route Guardian, a reliable securityoriented SDN routing mechanism, which considers the capabilities of SDN switch nodes combined with a Network Security Virtualization framework. Our scheme employs the distributed network security devices effectively to ensure analysis of abnormal traffic and malicious node isolation. Furthermore, Route Guardian supports dynamic routing reconfiguration according to the latest network status. We prototyped Route Guardian and conducted theoretical analysis and performance evaluation. Our results demonstrate that this approach can effectively use the existing security devices and mechanisms in SDN.

关键词： Software-Defined Networking(SDN) network security virtualization capacity-based routing security oriented routing dynamic routing reconfiguration

Effective local dynamic routing strategy for air route networks

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Chinese Journal of Aeronautics 2015年第6期28卷 1709-1717页

作者： Wu Wenjun Zhao Lingxi school of Electronic and information engineering Beihang University

With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network （ARN）, we propose an effective local dynamic routing strategy in this paper. Several factors, such as the rout- ing distance, the geographical distance and the real-time local traffic, are taken into consideration. When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing （SPR） strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network （CARN） is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.

关键词： Air route network Air transportation Dynamic routing Network throughput Routing strategies

Feedforward Neural Network Models for FPGA Routing Channel Width Estimation

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Chinese Journal of Electronics 2016年第1期25卷 71-76页

作者： LIU Qiang GAO Ming ZHANG Tao ZHANG Qijun school of Electronic information engineering Tianjin University

Since interconnects play the increasingly important role in delay and area of the Fieldprogrammable gate array(FPGA) implementations, routing architecture design has become the focus of much work related to FPGA architecture development. This paper leverages feedforward neural networks to derive accurate models of the routing channel width in homogeneous FPGA architecture with two advanced intelligence learning techniques: Gradient-based learning algorithm(GLA) and Extreme learning machine(ELM). The resultant models can be used in the early stages of FPGA architecture development to facilitate fast design space exploration which is difficult to achieve in the traditional experiment-based method. The proposed models are evaluated by comparing the estimated channel widths to the real values generated from a CAD tool VTR over IWLS2005 benchmark circuits. Results show that the GLA model achieves the estimation accuracy 3.98% and the ELM model has the accuracy 3.91%, which show significant improvement over existing estimation approaches.

关键词： Field-programmable gate array(FPGA) architecture design Feedforward neural network Routing channel width estimation

An Improved Ionospheric Spatial Threat Model for SBAS

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Chinese Journal of Electronics 2017年第5期26卷 1105-1110页

作者： ZHANG Qidong LI Rui WANG Zhipeng school of Electronic and information engineering Beihang University

A conservative Grid ionospheric vertical delay error(GIVE) estimation would lead to conservative Protection levels(PLs) estimation and affects Satellitebased augmentation systems(SBAS) service *** reduce the margin in GIVE estimation,an improved spatial threat model is presented.A new parameter of Minimum separation distance(MSD) is *** new model is described with the MSD,Relative centroid metric(RCM) and fit radius as *** delay measurements during storms are used to construct the new spatial threat *** results show that,with the new model,there is at least 9.5% reduction in User ionospheric vertical delay errors(UIVEs),while the user ionospheric delay estimation errors can be bounded at the same *** on severe ionosphere disturbed days,at least 5% improvement of PLs(95%) could be achieved for more than20% Conterminous united states(CONUS) area,leading to higher system service performance.

关键词： Spatial threat model Grid ionospheric vertical delay error(GIVE) Minimum separation distance

Synthesis and room-temperature NO_2 gas sensing properties of a WO_3 nanowires/porous silicon hybrid structure

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Chinese Physics B 2014年第5期23卷 600-606页

作者：曾鹏张平胡明马双云闫文君 school of Electronics and information engineering Tianjin University

We report on the fabrication and performance of a room-temperature NO2 gas sensor based on a WO3 nanowires/porous silicon hybrid structure. The W18O49 nanowires are synthesized directly from a sputtered tungsten film on a porous silicon （PS） layer under heating in an argon atmosphere. After a carefully controlled annealing treatment, WO3 nanowires are obtained on the PS layer without losing the morphology. The morphology, phase structure, and crystallinity of the nanowires are investigated by using field emission scanning electron microscopy （FESEM）, X-ray diffractometer （XRD）, and high-resolution transmission electron microscopy （HRTEM）. Comparative gas sensing results indicate that the sensor based on the WO3 nanowires exhibits a much higher sensitivity than that based on the PS and pure WO3 nanowires in detecting NO2 gas at room temperature. The mechanism of the WO3 nanowires/PS hybrid structure in the NO2 sensing is explained in detail.

关键词： gas sensing WO3 nanowires porous silicon hybrid structure

Joint Communication-Caching-Computing Resource Allocation for Bidirectional Data Computation in IRS-Assisted Hybrid UAV-Terrestrial Network

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Chinese Journal of Electronics 2024年第4期33卷 1093-1103页

作者： Yangzhe LIAO Lin LIU Yuanyan SONG Ning XU school of information engineering Wuhan University of Technology

Joint communication-caching-computing resource allocation in wireless inland waterway communications enables resource-constrained unmanned surface vehicles(USVs) to provision computation-intensive and latencysensitive tasks forward beyond fifth-generation(B5G) and sixth-generation(6G) era. The power of such resource allocation cannot be fully studied unless bidirectional data computation is properly managed. A novel intelligent reflecting surface(IRS)-assisted hybrid UAV-terrestrial network architecture is proposed with bidirectional tasks. The sum of uplink and downlink bandwidth minimization problem is formulated by jointly considering link quality, task execution mode selection, UAVs trajectory, and task execution latency constraints. A heuristic algorithm is proposed to solve the formulated challenging problem. We divide the original challenging problem into two subproblems, i.e., the joint optimization problem of USVs offloading decision, caching decision and task execution mode selection, and the joint optimization problem of UAVs trajectory and IRS phase shift-vector design. The Karush–Kuhn–Tucker conditions are utilized to solve the first subproblem and the enhanced differential evolution algorithm is proposed to solve the latter one. The results show that the proposed solution can significantly decrease bandwidth consumption in comparison with the selected advanced algorithms. The results also prove that the sum of bandwidth can be remarkably decreased by implementing a higher number of IRS elements.

关键词： Wireless communication Heuristic algorithms Bandwidth Network architecture Downlink Trajectory Resource management

Knowledge-based detection method for SAR targets

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Journal of Systems engineering and Electronics 2014年第4期25卷 573-579页

作者： Fei Gao Achang Ru Jun Wang Shiyi Mao school of Electronic and information engineering Beihang University

When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.

关键词： synthetic aperture radar (SAR) target detection,knowledge-based improved genetic algorithm-fuzzy C-means(GA-FCM) algorithm.