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Frequency Agile Strategy Design of Radar Network for Wideband Sweep Jamming via Coalition Formation Game

IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 7906-7919页

作者： Liao, Maosen Xiong, Kui Zhang, Long Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China School of Information and Communication Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Chengdu611731 China

This article proposes an intelligent frequency agile design strategy for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several non-overlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multi-agent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile design strategy, a joint coalition formation game and distributed Q-learning algorithm (CFDQ) is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies. © 1965-2011 IEEE.

关键词： Jamming

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Model-based deep learning for fiber bundle infrared image restoration

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Defence technology（防务技术） 2023年第9期27卷 38-45页

作者： Bo-wen Wang Le Li Hai-bo Yang Jia-xin Chen Yu-hai Li Qian Chen Chao Zuo Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense Nanjing University of Science and TechnologyNanjingJiangsu Province210094China Smart Computational Imaging(SCI)Laboratory Nanjing University of Science and TechnologyNanjingJiangsu Province210094China Science and Technology on Electro-Optical Information Security Control Lab Tianjin300308China

As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual *** to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio(SNR)imaging in fiber bundles,the iterative super-resolution reconstruction network based on a physical model is *** the constraint of solving the two subproblems of data fidelity and prior regularization term alternately,the network can efficiently“regenerate”the lost spatial resolution with deep *** building and calibrating a dual-path imaging system,the real-world dataset where paired low-resolution(LR)-high-resolution(HR)images on the same scene can be generated *** results on both the United States Air Force(USAF)resolution target and complex target objects demonstrate that the algorithm can restore high-contrast images without pixilated *** the basis of super-resolution reconstruction,compound eye image composition based on fiber bundle is also embedded in this paper for the actual imaging *** proposed work is the first to apply a physical model-based deep learning network to fiber bundle imaging in the infrared band,effectively promoting the engineering application of thermal radiation detection.

关键词： Fiber bundle Deep learning Infrared imaging Image restoration

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Optimization of the Internet of Remote Things Data Acquisition Based on Satellite UAV Integrated Network

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China communications 2023年第7期20卷 15-28页

作者： Yuanyuan Yao Dengyang Dong Sai Huang Chunyu Pan Shuo Chen Xuehua Li Key Laboratory of Information and Communication Systems Ministry of Information IndustryBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement&Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China

In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things(IoRT),we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle(UAV)-low earth orbit(LEO)satellite integrated space-air-ground network,in which the UAV acquires data from massive Internet of Things(IoT)devices in special *** combine with the actual scenario,we consider two different data types,that is,delay-sensitive data and delay-tolerant data,the transmission mode is accordingly divided into two *** delay-sensitive data,the data will be transmitted via the LEO satellite relay to the data center(DC)in *** delay-tolerant data,the UAV will store and carry the data until the acquisition is completed,and then return to *** to nonconvexity and complexity of the formulated problem,a multi-dimensional optimization Rate Demand based Joint Optimization(RDJO)algorithm is *** algorithm first uses successive convex approximation(SCA)technology to solve the non-convexity,and then based on the block coordinate descent(BCD)method,the data acquisition efficiency is maximized by jointly optimizing UAV deployment,the bandwidth allocation of IoRT devices,and the transmission power of the ***,the proposed RDJO algorithm is compared with the conventional *** consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation,UAV deployment and the transmission power.

关键词： Internet of Remote Things dataacquisi-tion unmanned aerial vehicle LEO satellite

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Adaptive Time Slot Resource Allocation in SWIPT IoT Networks

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Computer Modeling in Engineering & sciences 2023年第9期136卷 2787-2813页

作者： Yunong Yang Yuexia Zhang Zhihai Zhuo Key Laboratory of Information and Communication Systems Ministry of Information IndustryBeijing Information Science and Technology UniversityBeijing100101China Key Laboratory of ModernMeasurement&Control Technology Ministry of EducationBeijing Information Science&Technology UniversityBeijing100101China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing100101China

The rapid advancement of Internet of Things(IoT)technology has brought convenience to people’s lives;however further development of IoT faces serious challenges,such as limited energy and shortage of network spectrum *** address the above challenges,this study proposes a simultaneous wireless information and power transfer IoT adaptive time slot resource allocation(SIATS)***,an adaptive time slot consisting of periods for sensing,information transmission,and energy harvesting is designed to ensure that the minimum energy harvesting requirement ismet while the maximumuplink and downlink throughputs are ***,the optimal transmit power and channel assignment of the system are obtained using the Lagrangian dual and gradient descent methods,and the optimal time slot assignment is determined for each IoT device such that the sum of the throughput of all devices is *** results show that the SIATS algorithm performs satisfactorily and provides an increase in the throughput by up to 14.4%compared with that of the fixed time slot allocation(FTS)*** the case of a large noise variance,the SIATS algorithm has good noise immunity,and the total throughput of the IoT devices obtained using the SIATS algorithm can be improved by up to 34.7%compared with that obtained using the FTS algorithm.

关键词： Internet of Things simultaneous wireless information and power transfer adaptive time slot resource allocation

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C2P-Net: Comprehensive Depth Map to Planar Depth Conversion for Room Layout Estimation

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第07期47卷 5350-5367页

作者： Zhang, Weidong Zhou, Mengjie Cheng, Jiyu Liu, Ying Zhang, Wei Xi'an University of Posts & Telecommunications School of Communications and Information Engineering China Xi'an Key Laboratory of Image Processing Technology and Applications for Public Security China Shandong University School of Control Science and Engineering China Ministry of Education Key Laboratory of Machine Intelligence and System Control China

Room layout estimation seeks to infer the overall spatial configuration of indoor scenes using perspective or panoramic images. As the layout is determined by the dominant indoor planes, this problem inherently requires the reconstruction of these planes. Some studies reconstruct indoor planes from perspective images by learning pixel-level or instance-level plane parameters. However, directly learning these parameters has the problems of susceptibility to occlusions and position dependency. In this paper, we introduce the Comprehensive depth map to Planar depth (C2P) conversion, which reformulates planar depth reconstruction into the prediction of a comprehensive depth map and planar visibility confidence. Based on the parametric representation of planar depth we propose, the C2P conversion is applicable to both panoramic and perspective images. Accordingly, we present an effective framework for room layout estimation that jointly learns the comprehensive depth map and planar visibility confidence. Due to the differentiability of the C2P conversion, our network autonomously learns planar visibility confidence by constraining the estimated plane parameters and reconstructed planar depth map. We further propose a novel approach for 3D layout generation through sequential planar depth map integration. Experimental results demonstrate the superiority of our method across all evaluated panoramic and perspective datasets. © 1979-2012 IEEE.

关键词： Layout Three Dimensional Displays Image Reconstruction Estimation Cameras Floors Cognition Transforms Training Semantics Room Layout Estimation Monocular Depth Estimation Planar Depth Reconstruction Planar Visibility Confidence Function Of Depth Comprehensive Function Room Layout Depth Planes Depth Conversion Layout Estimation Sequence Mapping Integration Of Sequences Joint Learning Panoramic Images Planar Graphs Parameter Plane Visible Light Validation Set Intersection Over Union Probability Function Training Images Weight Coefficient Output Channels Depth Values Adjacent Walls Planar Regions Semantic Labels Pixel Coordinates Dice Loss Non Planar Surfaces Depth Estimation Global Vision Camera Pose Camera Coordinate System

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PMB filter based distributed tracking of multiple extended targets under different resolutions 100

PMB filter based distributed tracking of multiple extended t...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Li, Yue Gao, Lin Wei, Ping Li, Wanchun Zhang, Huaguo Mu, Hao University of Electronic Science and Technology of China School of Information and Communication Engineering China National Key Laboratory of Electromagnetic Space Security China

ISBN: (纸本)9798331517786

A key feature of extended target (ET) is that it can produce multiple measurements, thus providing detailed information such as size, orientation. However, due to the measurement number decrease, the ET tends to be a point target (PT) when it becomes far from the sensor, leading to disability of estimating the extensions. In this paper we consider the problem of distributed ETs tracking based on multiple sensors. In such a case the measurements decrease of an ET can be compensated by other sensors, so that the tracking performance can be maintained. In the proposed algorithm the targets are modeled by Poisson multi-Bernoulli (PMB) random finite set (RFS) and the state of each target consists of two parts representing the possibility of being ET and PT, respectively. In the local filtering state, interaction between ET and PT states is considered in the prediction step for target identity change between ET and PT, based on which the local PMB filter is achieved for seamlessly tracking ETs and PTs. In the fusion part a generalized covariance intersection (GCI) based criterion is proposed to fuse the posteriors of each sensor. The performance of proposed algorithm is verified via simulations. © 2024 IEEE.

关键词： Target tracking

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Artificial Intelligence-Aid OTFS Receiver: Design and Performance Evaluation

Artificial Intelligence-Aid OTFS Receiver: Design and Perfor...

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2023 International Conference on Ubiquitous communication, Ucom 2023

作者： Wang, Chenxi Qian, Li Ping Zhu, Huijie College of Information Engineering Zhejiang University of Technology Hangzhou China The 36th Research Institute of China Electronics Technology Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9798350340433

OTFS technology is attracting much attention due to its strong adaptability to high-speed mobility and high spectrum efficiency. Studies show that applying deep learning (DL) to traditional communication systems significantly improves their performance. To this end, this paper proposes an AI-Aid OTFS receiver to enhance the performance of OTFS systems in high-speed mobile communication scenarios. The proposed receiver employs two networks-a channel estimation network called TFNet and a decoding network called RecovNet. In the channel estimation module, TFNet performs more accurate channel estimation based on the results of traditional channel estimation methods. In the decoding module, RecovNet decodes the signal based on the equalized signals. To validate the superiority of our proposed receiver, we conduct comparative testing with a traditional receiver under the integer Doppler channel. The experimental results demonstrate that integrating DL technology in OTFS systems effectively enhances their performance. © 2023 IEEE.

关键词： Decoding

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Influence of Physical Parameters on Echo Spectrum of Underwater Target

Influence of Physical Parameters on Echo Spectrum of Underwa...

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2024 OES China Ocean Acoustics, COA 2024

作者： Chen, Yunfei Yu, Dapeng Jia, Bing Wang, Zhenshan Yong, Jintao Wang, Yanjie School of Information and Communication Engineering Dalian University of Technology Dalian China Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (纸本)9798350340297

The elastic scattering features of the underwater target scattering wave depend on the physical parameters of the target, such as the material and structure. Intuitively evaluating the influence of the elastic scattering wave on the characteristics of the whole scattering wave signal is difficult due to the coupling and superposition of the elastic scattering wave and the geometric scattering wave of the target. Based on the different modulation characteristics of broadband echo spectrum produced by target geometry scattering and elastic scattering wave, this paper characterizes and studies the modulation features of echo spectrum and tests the influence of physical parameters on the echo spectrum of underwater target using several simple cylindrical targets with different physical parameters. Moreover, the geometric scattering wave and the elastic scattering wave of the simple target echo are extracted using the fractional Fourier transform (FrFT) domain filtering method, and the influence of physical parameters on the echo spectrum is quantitatively analyzed. © 2024 IEEE.

关键词： Elastic scattering

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DFT-SPREAD COMBINED WITH PTS METHOD TO REDUCE THE PAPR IN RADCOM SYSTEM 10

DFT-SPREAD COMBINED WITH PTS METHOD TO REDUCE THE PAPR IN RA...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Zhi, Ruxin Quart, Cong Xu, Zhan Yang, Xiaolong Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

In radar communication integration (RADCOM) systems based on orthogonal frequency division multiplexing (OFDM) technology, high peak to average power ratio (PAPR) is one of the main factors affecting system performance. This article analyses the PAPR probability distribution of radar communication integrated signals based on OFDM. In order to reduce the PAPR of integrated signals, the discrete Fourier transform spread spectrum (DFT Spread) technology suitable for traditional OFDM systems has been improved and combined with partial transmission sequences (PTS) to further reduce the PAPR of radar communication integrated signals. The simulation results show that compared with using DFT spread spectrum technology alone, PTS technology alone, and the original signal, the proposed DFT PTS joint algorithm based on linear interpolation reduces PAPR by 1.5 dB, 2.4 dB, and at least 4.1 dB, respectively. Obviously, the DFT-PTS joint algorithm achieved the best PAPR suppression effect. © The Institution of Engineering & technology 2024.

关键词： Orthogonal frequency division multiplexing

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Minimum dispersion beamforming using modified conjugate gradient method

Minimum dispersion beamforming using modified conjugate grad...

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2021 International Conference on Electronic information Engineering and Computer communication, EIECC 2021

作者： Song, Jinyang Wang, Wei Chen, Yan Science and Technology on Communication Information Security Control Laboratory China Cetc 36 Zhejiang Jiaxing China

ISBN: (数字)9781510653207

ISBN: (纸本)9781510653191

In order to solve linear constraint minimize dispersion problem in beamforming with non-Gaussian signals or noise, this paper proposed a real time adaptive beamforming technique based on modified conjugate gradient (MCG) method. Compared to conventional adaptive method, MCG have faster convergence rate than stochastic gradient (SG) method, and comparable convergence rate with recursive least square (RLS) method with lower complexity. And it simplifies the procedure of conjugate gradient method with one iteration per snapshots by using inexact line search scheme. Simulation has demonstrated the superior performance in output SINR and its convergence rate. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Beamforming

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