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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yingfei Wang Xiaoqin Xue Wei Wang Department of Computer Science Xi’an Polytechnic University Xi’an China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing China

An efficient radar signal processing parallel algorithm for Open Computing Language (OpenCL) is presented in this paper, which reveals a rational allocation schema of tasks between the central processing unit (CPU) and the graphics processing unit (GPU). The powerful parallel processing ability of GPU is used to replace the traditional serial processing method by the way of pipeline acceleration and algorithm parallel acceleration, and the real-time performance of the proposed algorithm is improved by the design idea of intra-module parallelism and inter-module flow processing. The algorithm is applied to CPU-GPU heterogeneous computing platform and has a good portability. The effectiveness and real-time performance of the algorithm are verified through simulation data.

关键词： Signal processing algorithms Graphics processing units Radar signal processing Real-time systems Heterogeneous networks Central Processing Unit Resource management

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Cone-Shaped Space Target Inertia Characteristics Identification by Deep Learning with Compressed Dataset

TechRxiv

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TechRxiv 2022年

作者： Li, Mengmeng Wang, Shaoran Yang, Tian Ai, Xia Liu, Jiaqi Andriulli, Francesco P. Ding, Dazhi Department of Communication Engineering Nanjing University of Science and Technology Nanjing China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing100076 China Politecnico di Torino of Turin Turin Italy

An effective method for identifying inertia characteristics of cone-shaped space target based on deep learning is proposed. The inertia ratio is determined by the time-varying scattering fields from the cone-shaped targets. The multistatic method is introduced to reduce the evaluation time of time-varying scattering fields. The micro-Doppler spectrogram (MDS) dataset is constructed by time-frequency analysis with numerical simulation method, point scattering model, and experimental tests. The compressed dataset is further achieved by truncated singular value decomposition (SVD). Finally, the micro-motion parameter identification model is constructed to identify the inertia ratio for the cone-shaped space target. The interaction loss function and the feed-forward denoising convolutional neural networks (DnCNNs) are employed to improve the identification accuracy. Parameters identification of the precession frequency, precession angle, spin frequency, and inertia ratio with both simulation and experiment datasets demonstrate the validity of the proposed method. © 2022, CC BY.

关键词： Singular value decomposition

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A Jamming Decision-Making Method Based on Next State Prediction SAC

A Jamming Decision-Making Method Based on Next State Predict...

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

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

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.

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Progress and prospective of electromagnetic periodic structures 4

Progress and prospective of electromagnetic periodic structu...

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Zhang, Shengjun Mu, Lei Shao, Chunshou Ai, Xia Wang, Weidong Chai, Song Cui, Yichun Liu, Shengdong Sun, Cuiyun Zhou, Nan Xie, Lei Li, Chunyu Jiao, Luting Wang, Yue Qi, Zhaohui Wang, Minghao Yong, Zhengyu Sun, Yuan Kong, Dewang National Key Laboratory of Science Technology on Test Physics and Numerical Mathematics Beijing China The Star of Aerospace Innovation Research Institute in Changsha Hunan Changsha China Beijing Institute of Space Long March Vehicles Beijing China Institute of Survival Technology Effectiveness Evaluation of Flying Vehicle Beijing China National Key Laboratory of Science Technology on Electromagnetic Scattering Beijing China

ISBN: (纸本)9781733509619

Periodic structures have attracted interests of researches for decades, and they were discovered more and more useful properties, and have been applied to many fields. Furthermore, more and more novel concept and phenomena based on periodic structures were proposed and found, such as tunable electromagnetic properties of some structures. In this paper, recent progress on two of the periodic structures, i.e., FSS and metamaterials and their variations, were revie, and the physical nature of these structures analog to materials were also suggested. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Periodic structures

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

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

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IEEE International Conference on Electronic Information and Communication technology (ICEICT)

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

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.

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Intra-pulse modulation feature analysis and parameter estimation of phase and frequency multi-modulation signal

Intra-pulse modulation feature analysis and parameter estima...

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IET International Radar Conference (IRC 2023)

作者： Chenle Xue Zhiye Jiang Lixiang Ren Huayu Fan Quanhua Liu Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing 100081 People's Republic of China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing Institute of Space Long March Vehicle Beijing 100076 People's Republic of China

ISBN: (数字)9781837240982

The parameter inversion of multi-modulation waveforms has always been a key and difficult problem in the field of electronic reconnaissance. To solve this problem, a method for intra-pulse modulation feature analysis and parameter estimation of phase and frequency multi-modulation signal is proposed in this paper. Firstly, we apply square preprocessing to eliminate the binary phase coded modulation information. Then, subpulse separation and subpulse parameter estimation are achieved by using the smooth pseudo-Wigner Ville distribution (SPWVD) and wavelet transform. Moreover, histogram statistics are introduced to improve the robustness of the method. Finally, the N-order phase difference is proposed for recovering binary phase coded sequences. Frequency domain filtering and sliding window averaging are also added to further improve the applicability of the proposed method under low signal-to-noise ratio (SNR) conditions. Simulation results suggest that the method proposed in this paper can achieve accurate signal inversion and has good robustness.

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Intercept Strategy for Maneuvering Target Based on Deep Reinforcement Learning

Intercept Strategy for Maneuvering Target Based on Deep Rein...

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第40届中国控制会议

作者： Xu Wang Yuanli Cai Yizhong Fang Yifan Deng School of Automation Science and Engineering Xi'an Jiaotong University National Key Laboratory of Science Technology on Test Physics & Numerical Mathematics

A novel interception strategy for high-speed maneuvering target based on reinforcement learning（RL） algorithm is proposed. With reshaped reward function and observation consisting solely of relative position information and path angle, the interception policy is trained by Deep Deterministic Policy Gradient（DDPG） algorithm. The results of training and test indicate that the proposed guidance law can approximate the optimal control model of the maneuvering target interception and show the superiority over traditional method.

关键词： Exoatmospheric Interception Maneuvering Target Deep Reinforcement Learning DDPG

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Low-overlap square aperture ptychography with selective scanning

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Optics and Laser technology 2025年 190卷

作者： Qiao, Ziling Wen, Xiu Chen, Hang Huang, Guancheng Zhou, Xuyang Li, Ziyang Ji, Yu Liu, Wei Chi, Dazhao Gao, Bin Liu, Shutian Xue, Feng Liu, Zhengjun Li, Yutong School of Physics Harbin Institute of Technology Harbin150001 China School of Physical Science and Technology Tiangong University Tianjin300387 China School of Space Information Space Engineering University Beijing101416 China Optical Imaging Laboratory Harbin Institute of Technology Shenzhen518055 China National Key Laboratory of Precision Welding & Joining of Materials and Structures Harbin Institute of Technology Harbin150001 China College of Data Science and Technology Heilongjiang University Harbin150080 China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beiiing100076 China

As an excellent representative of coherent diffraction imaging, ptychography iterative engine plays a crucial role in biomedical imaging and crystal structure analysis. However, the significant challenges regarding imaging speed and throughput have hindered its development in fast imaging. In this paper, we propose a fast square aperture reconstruction method with a low-overlap rate aimed at mitigating the issue of low efficiency. Our approach, employing the Tamura coefficient of gradient (TOG) operator-guided strategy with square aperture, surpasses the performance of previous initial iterations. Enhanced imaging quality is demonstrated by intentionally selecting patterns in the reconstruction stage. Our results illustrate that a high-overlap rate and extensive patterns are no longer indispensable for lensless ptychography. © 2025 Elsevier Ltd

关键词： Computational Imaging

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Sparse Conformal Array Synthesis Based on Multiagent Genetic Algorithm

Sparse Conformal Array Synthesis Based on Multiagent Genetic...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Ganyu Liu Hailiang Zhu Kai Wang Jinchao Mou Pei Zheng Gao Wei Northwestern Polytechnical University School of Electronics and Information Xi'an Shaanxi CN Beijing Research Institute of Telemetry Beijing CN The National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing CN

In this paper, multiagent genetic algorithm (MAGA) is firstly applied to tackle the synthesis of conformal sparse array, a constrained multi-objective optimization problem. Moreover, a model considered low peak sidelobe level (PSLL) is given for conformal sparse array synthesis. For the antenna array deployed on a quadric surface, the PSLL can be reduced by obtaining the optimal antenna element arrangement. An example of 256-element array synthesis with a 56% sparse rate proves MAGA as an effective optimization tool for conformal sparse arrays in low computational cost.

关键词： Computational efficiency Optimization Genetic algorithms Antenna arrays

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

Individual Identification Algorithm of Known Emitters Based ...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

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

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.

关键词： Convolution Simulation Neural networks Education Radar Reconnaissance Feature extraction

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