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6th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2023

作者： Chen, Geng Gao, Jingpeng Zhang, Tianran Jiang, Zhiye Shen, Chen College of Information and Communication Engineering Harbin Engineering University Harbin China Beijing Institute of Electronic System Engineering Beijing100854 China Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9798350399059

In light of the growing complexity of the electromagnetic environment, traditional jamming decision-making methods have become less effective due to poor generalization and inefficient jamming performance. This paper proposes a jamming decision-making method based on next state prediction SAC (Soft Actor-Critic) to address this issue. Firstly, we design the state, action, and reward elements under electronic warfare scenarios. Secondly, a next state prediction critic network is proposed to accurately estimate the value function by modeling the environment dynamics and extracting richer representational information. Finally, a negative activation ReLU is introduced to improve the utilization ratio of network parameters. Simulation results show that the proposed method achieves a 98.4% success rate at a distance of 90 km from the radar and a 70.0% success rate at 30 km. Therefore, this method exhibits good adaptability and jamming performance in the field of jamming decision-making. © 2023 IEEE.

关键词： Decision making

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Verification of Seasonal Prediction by the Upgraded China Multi-Model Ensemble Prediction System (CMMEv2.0)

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Journal of Meteorological Research 2024年第5期38卷 880-900页

作者： Jie WU Hong-Li REN Jianghua WAN Jingpeng LIU Jinqing ZUO Changzheng LIU Ying LIU Yu NIE Chongbo ZHAO Li GUO Bo LU Lijuan CHEN Qing BAO Jingzhi SU Lin WANG Jing-Jia LUO Xiaolong JIA Qingchen CHAO CMA Key Laboratory of Climate Prediction Studies National Climate CentreChina Meteorological Administration(CMA)Beijing 100081 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044 State Key Laboratory of Severe Weather and Institute of Tibetan Plateau Meteorology Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 CMA Earth System Modeling and Prediction Centre China Meteorological AdministrationBeijing 100081

Based on a combination of six Chinese climate models and three international operational models,the China multimodel ensemble(CMME)prediction system has been upgraded into its version 2(CMMEv2.0)at the national Climate Centre(NCC)of the China Meteorological Administration(CMA)by including new model members and expanding prediction products.A comprehensive assessment of the performance of the upgraded CMME during its hindcast(1993–2016)and real-time prediction(2021–present)periods is conducted in this *** results demonstrate that CMMEv2.0 outperforms all the individual models by capturing more realistic equatorial sea surface temperature(SST)*** exhibits better prediction skills for precipitation and 2-m temperature anomalies,and the improvements in prediction skill of CMMEv2.0 are significant over East *** superiority of CMMEv2.0 can be attributed to its better projection of El Niño–Southern Oscillation(ENSO;with the temporal correlation coefficient score for Niño3.4 index reaching 0.87 at 6-month lead)and ENSO-related *** for the real-time prediction in recent three years,CMMEv2.0 has also yielded relatively stable skills;it successfully predicted the primary rainbelt over northern China in summers of 2021–2023 and the warm conditions in winters of 2022/*** that,ensemble sampling experiments indicate that the CMMEv2.0 skills become saturated after the ensemble model number increased to 5–6,indicating that selection of only an optimal subgroup of ensemble models could benefit the prediction performance,especially over the extratropics,yet the underlying reasons await future investigation.

关键词： China multi-model ensemble(CMME)prediction system predictability source El Niño-Southern Oscillation(ENSO) real-time forecast verification

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An Absorptive/Transmissive Frequency Selective Surface with Wide Transmission Band and Low Insertion Loss

An Absorptive/Transmissive Frequency Selective Surface with ...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Hang Song Jiaqi Liu Shengjun Zhang National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics Beijing China

The Absorptive/transmissive Frequency Selective Surface (ATFSS) is a multi-layer composite periodic structure with out-of-band absorption and in-band transmission characteristics, usually composed of a lossy resistive sheet (RS) and a lossless bandpass FSS. In this paper, an equivalent circuit method based on transmission line theory was used to design the ATFSS with idea of higher frequencies for transmission and lower frequencies for absorption, as well as the impedance conditions for satisfying wave transmission and absorption. Furthermore, the S-parameters was fitted, which verifies the design concept. Finally, the simulation was performed with numerical method. It is shown from the simulation that the broadband absorption of the ATFSS ranges from 2.00 GHz to 6.29 GHz, and the broadband transmission ranges from 8.46 GHz to 11.32 GHz with an insertion loss of less than 1 dB.

关键词： Frequency selective surfaces Absorption Insertion loss Power system stability Propagation losses Stability analysis Broadband communication

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Semantic Segmentation Algorithm of Street View Image Via Deep Learning

Semantic Segmentation Algorithm of Street View Image Via Dee...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Zihui Zhu Wenlin Cai Jianhua Li Feng Xue Lu Gao Jiaqi Liu National Key Laboratory Science and Technology on Test Physics and Numerical Mathematics Beijing China

Real-time semantic segmentation of street view images can be used as a visual aid system during autonomous driving. This paper proposes a multi-branch cross-layer fusion network (MCFNet). The model uses a multi-branch network to extract features, fuses the features of different stages of multiple branches for prediction, and uses a lightweight depthwise separable convolution to reduce the amount of computation. We use the Cityscapes dataset to train and evaluate the algorithm and get 61.6% mIoU and 115.3 fps.

关键词： Cross layer design Visualization Convolution Semantic segmentation Roads Semantics Feature extraction

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Simulation and analysis of repeater deceptive jamming to SAR based on shift-frequency

Simulation and analysis of repeater deceptive jamming to SAR...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Daixuan Li Jiaqi Liu Jianhua Li Lu Gao Pei Zheng Zhonghang He National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

With the change of battlefield form, the pressure jamming requires the jammer to have large power, and the jamming efficiency is low, so the spoofing jamming comes into being. In this paper, the linear frequency modulation signal and fuzzy function are analyzed to verify the feasibility of using frequency shift forwarding to generate virtual images, and the two-dimensional frequency shift method is used to generate virtual images at specific locations to deceive local radar.

关键词： Analytical models Chirp modulation Frequency modulation Computational modeling Radar imaging Apertures Repeaters

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Ultra-wideband Magnetoelectric Dipole for 3G/LTE/Sub-6GHz 5G Applications

Ultra-wideband Magnetoelectric Dipole for 3G/LTE/Sub-6GHz 5G...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2022

作者： Liu, Ganyu Zhu, Hailiang Wang, Kai Qiu, Yuwei Mou, Jinchao Zheng, Pei Wei, Gao Northwestern Polytechnical University Shaanxi Xi'an710129 China The Beijing Research Institute of Telemetry Beijing100094 China The National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing100076 China

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A new ultra-wideband magnetoelectric (ME) dipole antenna is proposed as a dual-polarized base station antenna for 3G, LTE and Sub-6GHz 5G wireless networks. Double layers of ME dipoles with different sizes are combined to expand the bandwidth, and the orthogonal placement of ME dipoles enables dual polarization radiation. Simulation results reveal that the proposed base station antenna achieves 133.3% fractional bandwidth and satisfying radiation characteristics, including high front-to-back ratio (FBR) (>14 dB), high cross-polarization levels (>20 dB), and stable gains about 5-10 dBi in 1-5GHz. © 2022 IEEE.

关键词： Polarization

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Individual Identification Algorithm of Known Emitters Based on Lightweight Binary Channels Neural Network 12

Individual Identification Algorithm of Known Emitters Based ...

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12th International Conference on Information technology in Medicine and Education, ITME 2022

作者： Gao, Jingpeng Song, Xia Gao, Lu Harbin Engineering University College of Information and Communication Engineering Harbin China Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

ISBN: (纸本)9798350310153

Aiming at the problem that the traditional specific emitter identification method has poor feature extraction ability and limited recognition effect, this paper proposes a known specific emitter identification algorithm based on the LBCNet (the Lightweight Binary Channels Net). The algorithm uses bispectrum and cyclic spectrum to highlight the unintentional information in the pulse. Then, it combines the idea of depthwise separable convolution to design the LBCNet to realize adaptive feature extraction, fusion, and classification. Finally, it integrates the attention mechanism to highlight the effective information of the image, enhance the neural network's learning ability and improve the identification performance of specific emitters. The simulation results show that the recognition rate of the proposed algorithm is as high as 94.53% at 0dB, which has good engineering practical value and can be applied to the field of electronic reconnaissance. © 2022 IEEE.

关键词： Convolution

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Ellipse Fitting Based on Neural Network Optimization 41

Ellipse Fitting Based on Neural Network Optimization

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第41届中国控制会议

作者： Chenrong Long Peng Liu Qinglei Hu School of Automation Science and Electrical Engineering Beihang University National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing Institute of Space Long March Vehicle School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China.

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Ellipse fitting is to estimate the parameters of the ellipse from a set of coplanar points,but the geometric distance from the plane point to the elliptic curve is difficult to calculate *** paper proposes a neural network optimization-based algorithm to estimate the geometric distances from plane points to elliptic curves to solve the ellipse fitting ***,the neural network is firstly applied to train the geometric distance between the plane point and the standard ellipse,and then obtain the geometric distance between the plane point and the general ellipse through the rotation and translation ***,use minimizing the sum of the Euclidean distances from the plane point to the elliptic curve as the objective function,and finally use the gradient descent method to iteratively solve the ellipse ***,the proposed method avoids the direct algebraic solution of the geometric distance from the plane point to the elliptic curve and the performance of the algorithm to gether with its robustness to noise are analysed via numerical simulation.

关键词： Ellipse Fitting Coplanar Points Geometric Distance Neural Network Optimization

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A Binary Sparrow-Hybridized Beluga Whale Optimization Algorithm for Jamming Task Assignment 6

A Binary Sparrow-Hybridized Beluga Whale Optimization Algori...

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6th IEEE International Conference on Electronic Information and Communication technology, ICEICT 2023

作者： Shen, Chen Gao, Jingpeng Jiang, Zhiye Zhang, Tianran Chen, Geng College of Information and Communication Engineering Harbin Engineering University Harbin150050 China Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China Beijing Institute of Electronic System Engineering Beijing100854 China

ISBN: (纸本)9798350399059

In the context of non-cooperative electronic countermeasures, the problem of formulating effective jamming task assignments arises due to insufficient collaborative jamming resources. This paper proposes a binary sparrow- hybridized beluga whale optimization algorithm based on jamming task assignments. The algorithm combines the binary sparrow search algorithm(BSSA) and the binary beluga whale optimization(BBWO), which is set with multi-dimensional constraints in the time, frequency and spatial domains. To achieve the optimal strategy for collaborative interference task assignment, a fitness function is constructed using both radar coverage and the signal-to-jamming ratio received by each radar. When the number of UAVs is 7 and the number of radars is 10, the simulation results show that the optimization speed and accuracy of the proposed algorithm are significantly higher than the BSSA and BBWO. Therefore, the algorithm has good coverage and performance in the field of jamming task assignments. © 2023 IEEE.

关键词： Optimization

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Near-field Measurement Method for Electromagnetic Scattering of Electrically Large-scale Plasma

Near-field Measurement Method for Electromagnetic Scattering...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jiaqi Liu Lu Gao Runhui Wu Xia Ai Song Chai Xin Liu Shengjun Zhang Yichun Cui National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing China

In the near-field test environment of 01500×3300mm vacuum vessel with low electromagnetic scattering, the relative measurement method is used, that is, the results of electrically large-scale plasma radar cross s... 详细信息

关键词： Radar cross-sections Volume measurement Standards organizations Electromagnetic scattering Elementary particle vacuum Energy measurement Plasma measurements

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