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Anisotropic impedance holographic metasurface for near-field imaging

Photonics Research 2024年第10期12卷 2226-2234页

作者： XIANGSHUAI MENG HAOYU ZHANG TAO WU YU LI ANXUE ZHANG LEI RAN XIAOMING CHEN School of Information and Communications Engineering Xi’an Jiaotong UniversityXi’an 710049China Xi’an Institute of Space Radio Technology Xi’an 710199China National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China

In this paper,the concept of anisotropic impedance holographic metasurface is proposed and validated by realizing holographic imaging with multipoint focusing techniques in near-field areas at the radio frequency *** the microwave holographic leaky-wave theory and near-field focusing principle,the mapped geometrical patterns can be constructed based on the correspondence between meta-atom structural parameters and equivalent scalar impedances in this modulated *** from conventional space-wave modulated holographic imaging metasurfaces,this surface-wave-based holographic metasurface fed by monopole antenna embedded back on metal ground enables elimination of the misalignment error between the air feeding and space-wave-based metasurface and increase of the integration performance,which characterizes ultra-low profile,low cost,and easy *** core innovation of this paper is to use the classical anisotropic equivalent surface impedance method to achieve the near-field imaging effect for the first *** on this emerging technique,a surface-wave meta-hologram is designed and verified through simulations and experimental measurements,which offers a promising choice for microwave imaging,information processing,and holographic data storage.

关键词： surface holographic impedance

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radar Echo Modeling and Doppler Characteristic Fitting Method for UAVs Based on Multi-Scattering Point Model 2

Radar Echo Modeling and Doppler Characteristic Fitting Metho...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Xu, Li'Ang Jiang, Qi Wang, Rui Zhang, Jichuan Jiao, Longxiang Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Institute of Technology Advanced Technology Research Institute Beijing China

ISBN: (纸本)9798331515669

The radar echo characteristics of unmanned aerial vehicles provide important information for identification. The radar echoes of various types of UAVs are modeled by the multi-scattering point modeling method. A Doppler characteristic modeling method for unmanned aerial vehicles based on the mixture Gaussian algorithm is proposed, in which the slow-time dimension data are extracted from the Range- Doppler and fitted by the mixture Gaussian algorithm. The parameters of the Gaussian distribution components representing the unmanned aerial vehicle's Doppler spread characteristics are obtained using the algorithm. The simulated radar echoes of the multi-rotor unmanned aerial vehicle and the flapping-wing unmanned aerial vehicle are used for analysis. The performance of the fitting is acceptable and the way in which various parameters affect the Doppler characteristics is discussed and concluded. © 2024 IEEE.

关键词： Gaussian distribution

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Cross-Domain Detection Transformer with Multi-view Adaptive Feature Alignment in Remote Sensing Imagery 2

Cross-Domain Detection Transformer with Multi-view Adaptive ...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Wang, Shu Han, Jianhong Wang, Ying Hao, Xinyuan Luo, Zhaoyi Wang, Yupei Chen, Liang Beijing Institute of Technology National Key Laboratory for Science and Technology on Space-Born Intelligent Information Processing Beijing China Shanghai Academy of Spaceflight Technology Shanghai China

ISBN: (纸本)9798331515669

Unsupervised Domain Adaptation (UDA) techniques are crucial for remote sensing object detection, designed to address performance degradation caused by the domain gap between training and test data. These methods leverage unlabeled target domain data, thus alleviating the high costs associated with data annotation. Recent developments in Detection Transformers (DETR) have simplified the detection pipeline and attracted significant research interest. Building on this architecture, we introduce an unsupervised domain adaptation detector for remote sensing object detection. Specifically, we introduce a multi-view adaptive feature alignment module that initially captures domain-specific features in complex backgrounds by leveraging a cross-attention mechanism. Subsequently, we employ contrastive learning to enforce the aggregation of domain-specific features from various perspectives, thereby improving the accuracy of feature alignment. Moreover, we demonstrate that integrating the self-training framework into DETR-based detectors can significantly mitigate the domain gap by further utilizing unlabeled data in the target domain. We validated the effectiveness and generalizability of our method across two remote sensing cross-domain detection scenarios using four public datasets. © 2024 IEEE.

关键词： object detection remote sensing imagery Unsupervised domain adaptation

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Performance Analysis of the Space-time Adaptive processing for Distributed Space-borne Multiple-input Multiple-output radar 4

Performance Analysis of the Space-time Adaptive Processing f...

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4th International Conference on signal processing and Computer Science, SPCS 2023

作者： Yang, Zhiwei Wu, Xiangyu Li, Xianghai Jiang, Di Wu, Taisheng National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China

ISBN: (纸本)9781510672505

Space-time adaptive processing (STAP) has been extended to the distributed space-borne multiple-input multiple-output (MIMO) radar system to improve the detection performance. Nevertheless, the transmitting waveforms are not completely orthogonal to each other, resulting in the STAP performance deterioration. In this paper, we established a novel STAP performance analysis model to reveal the influence mechanism of waveform properties. Firstly, the signal model of distributed space-borne radar with hybrid baseline and yaw angle was presented. Then, we derived the characteristic of the clutter covariance matrix for post-Doppler STAP, considering the effect of waveform periodic auto-correlation and cross-correlation sidelobe. Finally, the numerical simulation results, based on indicators of clutter eigenvalue spectrum and output signal-to-noise ratio loss, demonstrated the accuracy of the proposed analysis model. The aforementioned results provide important basis for the design of distributed space-borne MIMO radar system. © 2023 SPIE.

关键词： Space time adaptive processing

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The Adjacency Codes of the First Yellow Graphs

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Journal of Systems Science & Complexity 2023年第4期36卷 1757-1768页

作者： SHI Minjia LI Shitao KIM Jon-Lark SOLE Patrick Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China School of Mathematical Sciences Anhui UniversityHefei 230026China Department of Math Sogang UniversitySeoulSouth Korea Aix Marseille Univ CNRSCentrale MarseilleI2MMarseilleFrance

The authors study the binary codes spanned by the adjacency matrices of the strongly regular graphs(SRGs)on at most two hundred vertices whose existence is *** authors show that in length less than one hundred they cannot be cyclic,except for the exceptions of the SRGs of parameters(85,42,20,21)and(96,60,38,36).In particular,the adjacency code of a(85,42,20,21)is the zero-sum *** the range[100,200]the authors find 29 SRGs that could possibly have a cyclic adjacency code.

关键词： Cyclic codes strongly regular graphs adjacency codes self-orthogonal codes

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Frequency Control Scheme for Target Tracking under Dynamic Electromagnetic Environment 2

Frequency Control Scheme for Target Tracking under Dynamic E...

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2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Zhang, Peng Yan, Junkun Wang, Jiaxing Pu, Wenqiang Dang, Xudong Liu, Hongwei Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Xidian University Hangzhou Institute of Technology Hangzhou China The Chinese University of Hong Kong Shenzhen Research Institute of Big Data Shenzhen China

ISBN: (纸本)9798331515669

This paper proposes a frequency control (FC) scheme for radar systems that aims to improve target tracking accuracy under dynamic jamming environments. Specifically, the radar must alter the transmit frequency to reduce the impact of jamming. To combat the dynamic jammer, we construct FC as a Markov Decision Process (MDP) within a reinforcement learning framework. By applying a policy iteration technique to the MDP, an optimal strategy can be learned guiding the radar how to choose the transmit frequency at every frame. Since the entire target tracking process is real-time, a trade-off method is to balance the relationship between the model update and FC scheme utilization until online tracking process is over. Simulation results indicate that the proposed method can evidently beat the dynamic jamming and improve the target tracking accuracy. © 2024 IEEE.

关键词： Markov processes

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Joint state-sharing and truncation BCJR for power-efficient coherent optical interconnections utilizing symbol-rate sampling DSP over a hollow-core fiber

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Optics Letters 2025年第10期50卷 3461-3464页

作者： Wang, Chenchen Li, Zhipei Dong, Ze Gao, Ran Song, Junyuan Mai, Tianle Guo, Dong Chang, Huan Pan, Xiaolong Zhu, Lei Xin, Xiangjun School of Information and Electronics Beijing Institute of Technology Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing100081 China School of Integrated Circuits Beijing University of Posts and Telecommunications Beijing100876 China

Power-efficient digital signal processing (DSP) architectures are indispensable for enabling the sustainable scalability of optical networks in next-generation data center interconnects (DCIs). This paper introduces a minimalist symbol-rate sampling (SRS) DSP framework for coherent optical systems, seamlessly integrated with a hollow-core fiber (HCF) to enable ultra-low-complexity signal processing. The core of this framework is the joint state-sharing and truncation Bahl–Cocke–Jelinek–Raviv (JSST-BCJR) algorithm, which enhances hardware efficiency by eliminating up to 91% of state-space computations, significantly reducing computational complexity while maintaining negligible performance degradation. Experimental validation confirms the feasibility of the proposed minimalist SRS-DSP framework through the successful transmission of a 100-Gbaud 16QAM signal over 20.6 km of HCF. This work underscores the viability of SRS-DSP in power-constrained DCIs and highlights the synergistic integration of low-complexity DSP and HCF, offering a pathway toward power-efficient, high-throughput optical networks. © 2025 Optica Publishing Group. All rights are reserved.

关键词： Network coding

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Imperceptible and Sparse Adversarial Attacks via a Dual-Population-Based Constrained Evolutionary Algorithm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第2期4卷 268-281页

作者： Tian, Ye Pan, Jingwen Yang, Shangshang Zhang, Xingyi He, Shuping Jin, Yaochu Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230088 China Anhui University School of Computer Science and Technology Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Hefei230601 China Anhui University Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Hefei230601 China Bielefeld University Faculty of Technology Bielefeld33619 Germany

The sparse adversarial attack has attracted increasing attention due to the merit of a low attack cost via changing a small number of pixels. However, the generated adversarial examples are easily detected in vision since the perturbation to each pixel is relatively large. To achieve imperceptible and sparse adversarial attacks, this article formulates a bi-objective constrained optimization problem, simultaneously minimizing the 0 and 2 distances to the original image, and proposes a dual-population-based constrained evolutionary algorithm to solve it. The proposed method solves the optimization problem by evolving two populations, where one population is responsible for finding feasible solutions (i.e., successful attacks) and the other one is to minimize both the 0 and 2 distances. Moreover, a population initialization strategy and two genetic operators are customized to accelerate the convergence speed. Experimental results indicate that the proposed method can achieve high success rates with low attack costs, and strikes a better balance between the 0 and 2 distances than state-of-the-art methods. © 2020 IEEE.

关键词： Evolutionary algorithms

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A Novel Parameter Estimation and Integration Framework for Range Ambiguous Space High-Speed Maneuvering Target 4

A Novel Parameter Estimation and Integration Framework for R...

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4th International Conference on signal processing and Computer Science, SPCS 2023

作者： Xu, Xingyuan Yang, Zhiwei Li, Xianghai Yu, Haoran Mao, Yongfei Jiang, Di National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing100094 China

ISBN: (纸本)9781510672505

For the long-range and high-speed maneuvering space target detection, its performance is constrained by two challenges, the coherent integration loss due to Range migration and Doppler frequency spread, the contradiction between Range Ambiguity, and Doppler bandwidth ambiguity. This paper proposed a novel parameter estimation and integration method to solve the above two issues. Firstly, the waveform diversity technique is used to solve the range ambiguity problem. Then a matched filter bank for high-speed targets that can calculate the range ambiguity number is designed. Next, coherent integration is successfully achieved by estimating the target motion parameters and compensating for the echo signal. Finally, a two-step search strategy is proposed to improve the parameter estimation process, numerical experiments have validated that the complexity of the algorithm is reduced while ensuring the accuracy of the parameter estimation. © 2023 SPIE.

关键词： Parameter estimation

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An Inverse Reinforcement Learning Method to Infer Reward Function of intelligent Jammer

An Inverse Reinforcement Learning Method to Infer Reward Fun...

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2023 IEEE International radar Conference, radar 2023

作者： Fan, Youlin Jiu, Bo Pu, Wenqiang Li, Kang Zhang, Yu Liu, Hongwei Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Shenzhen Research Institute of Big Data The Chinese University of HongKong Shenzhen518172 China

ISBN: (纸本)9781665482783

This paper takes into account a frequency-agile radar system designated as 'us' and an adversarial spot jammer designated as 'enemy', where the enemy jammer is modeled as an agent, and the radar's strategy is characterized by its state transition probability in a Markov decision process (MDP). To comprehend the underlying attack motives of an intelligent jammer, a radar system must infer the utility function of the jammer. To accomplish this, the radar system must gather a dataset of actions taken by the jammer through observation of their transmitted signal. Next, a maximum entropy inverse reinforcement learning approach is utilized to recover the jammer's reward function. After recovering the jammer's reward function, the radar can infer the jammer's attack intent, and develop appropriate anti-jamming strategies to effectively mitigate against the intelligent jammer. Simulation results demonstrate the efficacy of the proposed method. © 2023 IEEE.

关键词： Reinforcement learning

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