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21st Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2024

作者： Zhou, Yinnan Zhou, Hao Li, Luowei Chen, Siming Liu, Zhi Li, Xiang-Yang LINKE Lab School of Computer Science and Technology University of Science and Technology of China China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China China Department of Computer and Network Engineering The University of Electro-Communications Tokyo182-8585 Japan

ISBN: (纸本)9798331519186

WiFi-based technology is appealing for indoor localization due to the widely deployed infrastructures. Recently, path separation solutions have been proposed to address the multipath effects and achieve decimeter-level localization accuracy in line-of-sight (LoS) scenarios. However, these solutions experience serious performance degradation in non-line-of-sight (NLoS) scenarios, and couldn’t be used for mobile device tracking where continuous LoS/NLoS switching happens. In this paper, we propose SaTrack, a LoS/NLoS state-aware mobile device tracking system. SaTrack identifies LoS/NLoS states based on the diversity of the strongest estimated paths when using different reference antennas. With the observation of spatial aggregation and temporal continuity for the Tx-Rx direct path, SaTrack chooses the direct path through two-step clustering, i.e., clustering in the spatial domain to form candidates and clustering again in the temporal domain to select the winner. Extensive experiments are conducted to evaluate the effectiveness of SaTrack. In a typical indoor environment with abundant multipath, SaTrack achieves 0.64m and 1.27m for the median and 90th percentile tracking errors, outperforming the state-of-the-art (SOTA) solutions. © 2024 IEEE.

关键词： Wi-Fi

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Multi-scale network combined with multi-loss optimization for low-light image super-resolution reconstruction 5

Multi-scale network combined with multi-loss optimization fo...

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5th International Conference on Computer Vision and Data Mining, ICCVDM 2024

作者： Liu, Bofeng Yu, Haiyang Hu, Xiaojuan Li, Yanfeng School of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China Key Laboratory of Photoelectric Measurement & Control and Optical Information Transfer Technology Ministry of Education Changchun University of Science and Technology Jilin Changchun130022 China

ISBN: (纸本)9781510682863

The proposed super resolution reconstruction method aims to address the issues of missing detailed information in low light environments and poor recovery of high frequency details in reconstructed images. To fully extract the retained features of low-light images, a multi-scale feature fusion learning network is introduced, which utilizes convolution to extract shallow features and then extracts deep features through multiple cascaded multi-scale feature extraction modules. Additionally, an attention mechanism is incorporated to adaptively learn the importance of each channel and finally fuse the obtained shallow and multi-scale features. Furthermore, perceptual loss and edge loss are integrated into the loss function to optimize the network for high frequency texture details in the recovered image. Experimental results demonstrate that this method yields clearer edge structures and texture details after super-resolution reconstruction of images acquired in low light environments, outperforming other existing methods both visually and objectively. © 2024 SPIE.

关键词： Convolutional neural networks

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Ship Size Attribute Reconstruction Method Based on Multi-aircraft Collaborative Detection 7th

Ship Size Attribute Reconstruction Method Based on Multi-air...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Xiaozu, Li Qingxi, Chi Peng, Jiang Mengmeng, Han Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789819733316

For mixed-ship scenarios, traditional aircraft have limited ability to extract ship features due to the constraints of observation angles, making it difficult to effectively select the high-value ship targets. In this paper, a ship length and width reconstruction method adaptable to multi-aircraft cooperative detection is proposed, taking dual-aircraft radar cooperative detection as the research object. Under the premise of known heading, a ship size reconstruction model is established by combining the radial size information from different observation directions. Finally, the performance of the model under different detection conditions is analyzed. Simulation verification shows that the maximum length reconstruction error does not exceed 7.56% of the true length of the target, which can effectively restore the target size information and provide necessary support for effectively solving the problem of the high-value ship targets selection in mixed scenes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Ships

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Optimal matching based on singular value decomposition for star pattern recognition 8

Optimal matching based on singular value decomposition for s...

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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Liang, Jiang Shijie, An Yalei, Qi Shuizhong, Chen Shengwei, Zhang Science and Technology on Electro-Optical Control Laboratory Luoyang471009 China Luoyang Institute of Electro-Optical Equipment AVIC Luoyang471009 China Shenyang Aircraft Design and Research Institute AVIC Shenyang11000 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

For the purpose of improving the recognition rate and the anti-noise ability, a new star pattern recognition algorithm is proposed, which is based on optimal singular value decomposition matching. The algorithm can effectively solve the recognition failure caused by redundant matching results, which the triangle recognition algorithm and the pyramid algorithm can not. Compared with traditional star pattern recognition algorithms, the recognition rate and the anti-noise ability of the new algorithm proposed in this paper are improved. With the star position noise added (Gauss noise, mean=0, s=3pixel), the recognition rate is 98.91%, and the average recognition time assumption is 20.21ms. © 2022 SPIE

关键词： Singular value decomposition

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A Scene Matching Backtracking Location Method Based on Convergence Criterion 11th

A Scene Matching Backtracking Location Method Based on Conve...

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11th China Conference on Command and control, C2 2023

作者： Peng, Siting Jun, Ren lei, Li Ma, Yichao Yang, Yanjiao Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819990207

In this paper, the engineering problems in scene matching positioning system are studied, according to the scene matching positioning of satellite under the condition of denial, establish a volume of physical model, kalman filtering method of indirect filtering residual envelope method is adopted to improve the mismatching points out and jumping back and forth, filtering results using backtracking method to solve the problem of less The precise positioning of the aircraft's own position under the condition of satellite rejection is realized, so as to achieve accurate guidance and strike to the target. The simulation results show that the method described in this paper is effective and has good academic and engineering significance. © Chinese Institute of Command and control 2024.

关键词： Kalman filters

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Overview of Anti-jamming Strategy for UAV Radar in Naval Battlefields 7th

Overview of Anti-jamming Strategy for UAV Radar in Naval Bat...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Li, Wen Pei, Hu-Cheng Qu, Guang-Zhou Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789819733316

In modern naval battlefields, the use of limited jamming resources by ships has become increasingly flexible and variable, which greatly increased the difficulty of unmanned aerial vehicle (UAV) radar countermeasures. In order to further improve the anti-jamming ability of UAV radar, radar also needs to find strategic countermeasures. From the perspective of tactical use, this paper combs the general use strategy of typical jamming in naval battlefields, studies the corresponding anti-jamming strategy of radar, focuses on the role of radar target selection strategy in anti-jamming and the current situation of the application of game theory in anti-jamming, and regards the game between radar and ship as a real-time strategic countermeasure problem, Thus, the development direction of radar intelligent anti-jamming is put forward. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Game theory

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Research on Multi-radar Anti-jamming Strategy Allocation Method Under Small Risk Based on Game Theory 7th

Research on Multi-radar Anti-jamming Strategy Allocation Met...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

ISBN: (纸本)9789819733354

In order to counteract the impact of passive jamming in unmanned airborne radar for search and attack missions against ships at sea, and to enhance the overall striking effectiveness at the UAV swarm level, a method is proposed to take the jamming scenario formed by the release of jamming from the ship as its set of game strategies, so as to construct a static zero-sum game model of the ship and UAV swarm, and then to take the mixed-strategy Nash equilibrium solution of the game as the method for the allocation of multi-radar anti-jamming strategies in the UAV swarm, and further gives a calculation method of the mixed-strategy Nash equilibrium solution of the game in the presence of risk by establishing the fitness evaluation function, compared with the Nash equilibrium solution of the game under no risk, the solution obtained by this method can enhance the expected benefit of the UAV swarm and better meet the actual tactical needs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned aerial vehicles (UAV)

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Spatiotemporal optical vortices generation in the green and ultraviolet via frequency upconversion[Invited]

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Chinese Optics Letters 2023年第8期21卷 12-16页

作者：高雪晨赵雨薇王珏卢扬张家璇范锦涛胡明列 Ultrafast Laser Laboratory Key Laboratory of Opto-electronic Information Science and Technology of Ministry of EducationSchool of Precision Instruments and Opto-electronics EngineeringTianjin UniversityTianjin 300072China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300308China

As a newly discovered type of structured light,a spatiotemporal optical vortex(STOV),which is remarkable for its space–time spiral phase and transverse orbital angular momentum(OAM),has garnered substantial *** previous studies have focused on the generation,characterization,and propagation of STOVs,but their nonlinear frequency conversion remains largely ***,we experimentally demonstrate the generation of green and ultraviolet(UV)STOVs by frequency upconversion of a STOV carried near-infrared(NIR)pulse emitted by a high repetition rate Yb-doped fiber laser amplifier ***,we verify that the topological charge of spatiotemporal OAM(ST-OAM)is doubled along with the optical frequency in the second-harmonic generation(SHG)process,which is visualized by the diffraction patterns of the STOVs in the fundamental and second-harmonic ***,the space–time characteristic of NIR STOV is successfully mapped to UV STOV by sum-frequency mixing STOV at 1037 nm and Gaussian beams in the green ***,we observe the topological charges of the ST-OAM could be degraded owing to strong space–time coupling and complex spatiotemporal astigmatism of such *** results not only deepen our understanding of nonlinear manipulation of STOAM spectra and the generation of STOVs at a new shorter wavelength,but also may promote new applications in both classical and quantum optics.

关键词： ultraviolet spatiotemporal optical vortex second-harmonic generation sum-frequency generation

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High-resolution recognition of FOAM modes via an improved EfficientNet V2 based convolutional neural network

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Frontiers of physics 2024年第3期19卷 175-183页

作者： Youzhi Shi Zuhai Ma Hongyu Chen Yougang Ke Yu Chen Xinxing Zhou International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and ApplicationsSchool of Physics and ElectronicsHunan Normal UniversityChangsha 410081China Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communications School of Information Science and EngineeringHunan Institute of Science and TechnologyYueyang 414006China

Vortex beam with fractional orbital angular momentum (FOAM) is the excellent candidate for improving the capacity of free-space optical (FSO) communication system due to its infinite modes. Therefore, the recognition of FOAM modes with higher resolution is always of great concern. In this work, through an improved EfficientNetV2 based convolutional neural network (CNN), we experimentally achieve the implementation of the recognition of FOAM modes with a resolution as high as 0.001. To the best of our knowledge, it is the first time this high resolution has been achieved. Under the strong atmospheric turbulence (AT) (C_(n)^(2)=10^(-15)m^(-2/3)), the recognition accuracy of FOAM modes at 0.1 and 0.01 resolution with our model is up to 99.12% and 92.24% for a long transmission distance of 2000 m. Even for the resolution at 0.001, the recognition accuracy can still remain at 78.77%. This work provides an effective method for the recognition of FOAM modes, which may largely improve the channel capacity of the free-space optical communication.

关键词： OAM free-space optical communication deep learning convolutional neural network

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Mitigation of Non-stationary Jammings with Missing Samples for GNSS Using Sparse Representation

Mitigation of Non-stationary Jammings with Missing Samples f...

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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Ren, Yuetao Zhi, Yongfeng Zhang, Jun School of Automation Northwestern Polytechnical University Xi'an710072 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Global navigation satellite systems (GNSS) are widely used in most civil and military applications. However, GNSS receivers suffer from severe performance degradation when jammed by electromagnetic interference. This paper considers the mitigation problem of non-stationary jammings with missing samples for GNSS. We propose to reconstruct the interference by sparse representation utilizing the sparsity of jammings in the time-frequency (TF) domain. The GNSS signal is recovered by eliminating the reconstructed interference from the received signal. First, the instantaneous frequencies (IFs) of jammings are extracted from adaptive directional TF distributions. Then, we construct the over-complete atomic dictionary based on the estimated IFs. The interference is reconstructed by orthogonal matching pursuit (OMP) algorithm. The proposed method can achieve the mitigation of non-stationary jamming and the acquisition of GNSS signals in the presence of missing samples. We confirm the effectiveness of the algorithm by simulations. © 2022 IEEE.

关键词： Jamming

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