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A method of Robust low-angle target height and compound reflection coefficient joint estimation

Journal of Systems Engineering and Electronics 2022年第2期33卷 322-329页

作者： WANG Shenghua CAO Yunhe LIU Yutao School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710061China Science and Technology on Communication Networks Laboratory Shijiazhuang 050081China National Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China

It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation *** highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the *** this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle *** compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target *** algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient ***-nally,the experiment and simulation results demonstrate the validity of the proposed method.

关键词： low-angle target robust joint estimation compound reflection coefficient multipath direction of arrival(DOA)

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A weighted low-rank and sparse constraint-based multi-channel radar forward-Looking imaging Method

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12973-12987页

作者： Tang, Junkui Ran, Lei Zheng, Liu Xie, Rong Liu, Yan Han, Genquan Xidian University Xi'an7100071 China Xidian University Hangzhou Institute of Technology Hangzhou311200 China Xidian University National Laboratory of Radar Signal Processing Xi'an710071 China Xidian University School of Microelectronics Xi'an7100071 China

radar super-resolution imaging method with joint low-rank and sparse constraints has garnered increasing attention. However, in complex imaging scenarios, the low-rank property of the signal matrix is often not prominent, which limits the performance of directly applying low-rank constraints in super-resolution imaging. To address this issue, this paper proposes a weighted low-rank and sparse (WLRS) constraint-based multi-channel radar forward-looking super-resolution imaging method. First, the proposed method calculates weighting coefficients using the covariance matrix of radar echoes and applies weighted constraints to the signal matrix, thereby enhancing its low-rank property and significantly improving forward-looking super-resolution imaging performance. Then, in solving the optimization problem, the Alternating Direction Method of Multipliers (ADMM) is employed to decompose variables and reduce the complexity of the solution. To further enhance computational efficiency, the symmetry of the weighting matrix and the characteristics of the dictionary matrix in sparse imaging, specifically as a partial Fourier dictionary, are leveraged. A fast matrix inversion method based on eigenvalue decomposition is proposed to mitigate the computational complexity induced by super-resolution requirements. Finally, the effectiveness and superiority of the proposed method in complex scenarios are validated through comparative experiments on simulated and measured data. © 2008-2012 IEEE.

关键词： Eigenvalues and eigenfunctions

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A Two-step signal Registration Algorithm for Distributed radar with Censored Observations 2

A Two-step Signal Registration Algorithm for Distributed Rad...

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

作者： Dou, Fabing Zhou, Shenghua Gong, Min Zhao, Pengfei Yang, Jian Sui, Xin Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China China Academy of Launch Vehicle Technology Beijing100000 China

ISBN: (纸本)9798331515669

In a distributed radar system, a signal fusion-based target detection algorithm can yield better detection performance compared to traditional decision fusion-based algorithm, thus has drawn considerable attention. In practice, however, signal fusion-based detection algorithm for distributed radar encounters two primary challenges: one is excessive communication cost and the other is difficult to fuse locally unregistered signals which is usually ignored by existing researches. To resolve these challenges, this paper presents a two-step signal registration algorithm with locally censored observations. Specifically, only local signals exceeding an initial threshold are sent to a fusion center for signal registration. At the first step of this algorithm, Mahalanobis Distance is employed as a metric to identify physically admissible observations, referred to as candidate observations. At the second step, the maximum likelihood estimation criterion is applied to eliminate potential false alarms among these candidate observations, thus determining the final set of registered observations for signal fusion. Numerical results indicate that the algorithm presented herein is capable of efficiently tackling the signal registration problem as well as alleviating communication burden. Furthermore, it achieves nearly lossless detection performance in comparison with its unregistered counterpart. This algorithm can be applied to practical engineering applications, since the simulation parameters are aligned with real radar scenarios. © 2024 IEEE.

关键词： Maximum likelihood estimation

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Fast Super-Resolution DOA Estimation for Unknown Number of Radiation Sources Based on Complex Convolutional Neural Networks 2

Fast Super-Resolution DOA Estimation for Unknown Number of R...

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

作者： Ma, Hui Liu, Xianpeng Liu, Hongwei Yang, Junxiang Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Xian Institute of Electromechanical Information Technology Electromechanical Dynamic Control Laboratory Xi'an China

ISBN: (纸本)9798331515669

To address the high computational complexity of traditional Direction of Arrival (DOA) estimation techniques and the limitations of previous neural networks in handling fixed signal sources, a new signal processing model was developed. This model employs sparse representation methods and deep learning through complex convolutional neural networks(CCNN). Focused research on the array's performance under unknown radiation sources using the complex convolutional neural network algorithm for super-resolution DOA estimation was conducted in a PyTorch environment. The results indicate that the complex convolutional model has a lower DOA computation complexity and higher precision in handling unknown radiation sources. After incorporating sparse representation with sampled data through the CCNN model for DOA estimation, an improvement in estimation accuracy and a reduction in computational complexity were observed compared to methods relying solely on sparse representation. Additionally, this model can effectively detect incoming waves from unknown radiation sources, unlike previous neural networks. © 2024 IEEE.

关键词： Convolutional neural networks

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Unified Localization Method Without Prior Range Information of Moving Target

Unified Localization Method Without Prior Range Information ...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Gong, Weishuang Wang, Qi Li, Yachao Xidian University Xidian University Hangzhou Institute of Technology Hangzhou China Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798350355581

This paper proposes a unified localization method based on the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA), which can estimate the position and velocity of the target when it is in the near-field, or the direction of the target when it is in the far-field. We use the modified polar representation (MPR) to unify the far-field and near-field models to construct an optimal localization problem with two constraints and propose an algebraic solution. The method first uses the least squares method to find the initial value without considering the constraints. Then the constraints are used to build an optimization equation to reduce the error of the initial value and obtain the precise value. Simulation results show that the proposed algorithm is close to the Cramer-Rao lower bound (CRLB), verifying the performance. © 2024 IEEE.

关键词： Cramer-Rao bounds

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Overlapping community‐based particle swarm optimization algorithm for influence maximization in social networks

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CAAI Transactions on Intelligence technology 2023年第3期8卷 893-913页

作者： Lei Zhang Yutong Liu Haipeng Yang Fan Cheng Qi Liu Xingyi Zhang Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Intelligent Computing and Signal Processing of Ministry of EducationSchool of Computer Science and TechnologyAnhui UniversityHefeiChina School of Computer Science and Technology University of Science and Technology of ChinaHefeiChina

Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour *** the existing influence maximization methods,the community‐based ones can achieve a good balance between effectiveness and ***,this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping *** fact,many nodes in social networks are overlapping ones,which play more important role in influence *** this end,an overlapping community‐based particle swarm opti-mization algorithm named OCPSO for influence maximization in social networks,which can make full use of overlapping nodes,non‐overlapping nodes,and their interactive information is ***,an overlapping community detection algorithm is used to obtain the information of overlapping community structures,based on which three novel evolutionary strategies,such as initialisation,mutation,and local search are designed in OCPSO for better finding influential *** results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts(***,CMA‐IM,CIM,CDH‐SHRINK,CNCG,and CFIN).

关键词： computational intelligence data mining social network

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An Airborne Terahertz Ice Cloud Detection System

An Airborne Terahertz Ice Cloud Detection System

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2024 Applied Optics and Photonics China: Laser technology and Applications, AOPC 2024

作者： Lv, Rongchuan He, Zheng Gao, Wenyu Dang, Pengju He, Chen Ren, He Dou, Haofeng Li, Yinan Li, Hao Luo, Feng National Key Laboratory of Radar Signal Processing Xidian University Xi'an710100 China China Academy of Space Technology Xi'an Xi'an710100 China

ISBN: (数字)9781510687745

ISBN: (纸本)9781510687738

Ice clouds have a high coverage on the Earth's surface and significantly impact the Earth's energy balance, climate change, and weather evolution. The brightness temperature in the terahertz band is highly sensitive to the main detection factors such as ice-water path and ice particle size, making it the optimal frequency band for ice cloud detection. Against the backdrop of ice cloud detection, an airborne terahertz ice cloud detector has been designed and developed. The radiometer system utilizes a full power type with periodic calibration, the antenna subsystem employs a plane mirror antenna and quasi-optical feed network for feeding and receiving, and the receiver subsystem adopts a direct mixing reception mode. The performance indicators of the system have been tested and verified, with results showing that the system performance meets the requirements of ice cloud detection. © 2024 SPIE.

关键词： Antenna feeders

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Digital Coding technology for Harmonic Control of Meta-Atoms

Digital Coding Technology for Harmonic Control of Meta-Atoms

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2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024

作者： Hou, Xinan Xi, Rui Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Hangzhou Institute of Technology Xidian University Hangzhou311200 China

ISBN: (纸本)9798350383317

With the progress of meta - atoms, digital coding technology has become an important branch of this research field with its advantage in establishing the connection between digital information and meta-atoms, which greatly simplifies the metaatom design. In this paper, a digital coding technique for harmonic generation and regulation is introduced. Firstly, the harmonic number is modified by changing the phase slope, and then the corresponding harmonic amplitude and phase are regulated by designing the coding control. The introduced digital coding technique gets rid of the problem of harmonic crosstalk existing in the traditional multi-frequency control technology, and at the same time make the beam control more flexible, which greatly improves the efficiency of communication. © 2024 IEEE.

关键词： Atoms

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Time Modulation in Phase Switching Screen for Target Stealth

Time Modulation in Phase Switching Screen for Target Stealth

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2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024

作者： Wang, Xueyan Xi, Rui Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China Hangzhou Institute of Technology Xidian University Hangzhou311200 China

ISBN: (纸本)9798350383317

Phase-switched screens (PSS) has the characteristics of dynamic regulatory radar scattering direction, and traditional PSS can only analyze the reflection state under infinite large size without considering the angle scattering. Here we introduce the time modulation theory to PSS for corner scattering analysis, which can realize the frequency spectrum movement of the target stealth in radar-tar get-receiver chanel transmission. The simulation analysis can be realized without signal reflection at the center frequency by switching different array elements. When the opposite phase array reaches the opposite, the sidelobes of the diagonal diagram can be effectively suppressed. © 2024 IEEE.

关键词： phase-switched screens target stealth time modulation

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Identifying important nodes of hypergraph:An improved PageRank algorithm

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Chinese Physics B 2025年第4期34卷 162-171页

作者： Yu-Hao Piao Jun-Yi Wang Ke-Zan Li School of Mathematics and Computing Science Guilin University of Electronic TechnologyGuilin 541004China School of Information and Communication Guilin University of Electronic TechnologyGuilin 541004China Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin University of Electronic TechnologyGuilin 541004China

Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important *** this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important nodes in a directed *** algorithm introduces the Jaccard similarity of directed *** comparing the numbers of common neighbors between nodes with the total number of their neighbors,the Jaccard similarity measure takes into account the similarity between nodes that are not directly connected,and can reflect the potential correlation between *** improved susceptible–infected(SI)model in directed hypergraph is proposed,which considers nonlinear propagation mode and more realistic propagation *** addition,some important node evaluation methods are transferred from undirected hypergraphs and applied to directed ***,the ImPageRank algorithm is used to evaluate the performance of the SI model,network robustness and *** of real networks demonstrate the excellent performance of the proposed algorithm and provide a powerful framework for identifying important nodes in directed hypergraphs.

关键词： hypergraph important node PageRank susceptible-infected(SI)model centrality index

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