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4th International Conference on Computer science and Communication technology, ICCSCT 2023

作者： Liu, Yali Xiong, Wei Xiong, Minghui Yu, Xiaolan Liu, Zheng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9781510671232

The optimization of reconnaissance constellation is an important step in the construction of space-based information system, and the coverage performance is the key index of the optimization of reconnaissance constellation. However, the coverage performance of the current constellation is mostly obtained through the simulation system, which has high time complexity and low efficiency, seriously slowing down the speed of constellation optimization. In order to improve the efficiency of constellation optimization, a two-stage optimization scheme of reconnaissance constellation based on machine learning is proposed. First, the trained machine learning prediction model is combined with the evolutionary algorithm to carry out rough optimization of the reconnaissance constellation, and the decision variable space after the scope is reduced is obtained. Then, in the reduced decision variable space, the simulation system and evolutionary algorithm are used to further optimize the problem, and the final result is obtained. The scheme proposed in this paper speeds up the convergence of population by reducing the search space of decision variables, thus improving the optimization efficiency. By comparing the optimization results of this scheme with those of the traditional scheme, it is found that the proposed scheme is 78.21% shorter than that of the traditional scheme under the premise that the quality gap between the optimization results of the traditional scheme and the traditional scheme is acceptable, which greatly improves the optimization speed of the reconnaissance constellation, and verifies the effectiveness and advancement of the proposed scheme. © 2023 SPIE.

关键词： Multiobjective optimization

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Research on Modeling of spatial information Network based on combat ring 3

Research on Modeling of spatial information Network based on...

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3rd International Conference on Digital Signal and Computer Communications, DSCC 2023

作者： Di, Lu Zhongwen, Zhao Yaru, Wang Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

Spatial information network itself is a comprehensive information network with multiple functions, which plays an important role in information acquisition, attack support, navigation and positioning, etc. In order to describe the function of spatial information network in detail, the combat ring theory is introduced to model the nodes, inter-satellite links and earth-satellite links of the network. At the same time, due to its complex and dynamic nature, Different from conventional combat network, the time accumulation graph model is introduced to further describe the network model, so as to truly reflect the support and attack capability of spatial information network under the combat background. © 2023 SPIE.

关键词： Graph theory

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MilChat: A Large Language Model and Application for Military Equipment 7

MilChat: A Large Language Model and Application for Military...

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7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Xue, Liu Jie, Liu Peipei, Zhu Tao, Xiang Southwest China Institute of Electronic Technology National Key Laboratory of Complex Aviation System Simulation Chengdu China

ISBN: (纸本)9798350354973

To offer the military personnel a good service of assisting them to get information about enemy's equipment outside Internet, we build a system named MilChat which includes a large language model that has the ability to generate texts and an application which is easy to use. The model of MilChat is fine-tuned by the method of LoRA with military datasets from the basic model, Qwen-7B-Chat which is opensource and has good performance. After fine-tuning, the new model has higher scores than the basic one. Besides, we use the method of Prompt Learning to limit the answers into a standard format. Therefore, it is more accurate and professional than the basic model. This study has also a value of industrial application. © 2024 IEEE.

关键词： Military equipment

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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12572-12587页

作者： Lin, Qinjie Sun, Hao Xu, Yanjie Wang, Junyu Ji, Kefeng Kuang, Gangyao National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Changsha410073 China

Automatic target recognition (ATR) is crucial for synthetic aperture radar (SAR) image interpretation. However, existing SAR ATR primarily rely on algorithms from the field of computer vision, many methods have not adequately considered the imaging sensitivity of SAR images. Moreover, SAR ATR typically follows the closed set assumption, but in dynamic and open real-world environments, SAR systems may encounter target classes that have not been seen during training. To address these issues, this paper proposes a SAR open set recognition (OSR) method that combines local electromagnetic scattering and global structure features. The global structural features focus on the overall relationship between target and background, while the local electromagnetic scattering features can effectively capture the scattering characteristics of target. Hence, we construct a global and local feature guidance (GLGE) network, fuses these complementary features as prior knowledge to guide deep features. Then, a class-anchor-based loss function is constructed by Anchor loss and Tuple loss, which cluster the features of known classes targets around predefined class anchors. Finally, the distance ratio is calculated to identify known classes targets and reject unknown classes targets. The experimental results on the MSTAR and SAR-ACD datasets show that our method outperforms other OSR methods in recall, precision, F1, and accuracy, demonstrating a superior performance in OSR. © 2008-2012 IEEE.

关键词： Automatic target recognition

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Fast measurement and prediction method for electromagnetic susceptibility of receiver

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Journal of systems Engineering and electronics 2024年第2期35卷 275-285页

作者： CHEN Yan LU Zhonghao LIU Yunxia State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and TechnologyNational University of Defense TechnologyChangsha 410073China State Key Laboratory of Astronautic Dynamics Xi’an 710043China

Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone ***,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent ***,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the *** experiment performed on a radar receiver confirms the reliability of the method proposed in this *** shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity *** on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.

关键词： electromagnetic susceptibility(EMS) receiver dualchannel multi-frequency nonlinear response frequency domain power domain

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Multi-View Subspace Clustering Via Simultaneously Cycle Projection and Similarity Learning 21

Multi-View Subspace Clustering Via Simultaneously Cycle Proj...

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21st International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Tao, Xiang Jie, Liu Wenshen, Qiao Siying, Xiao Mao, Ye Southwest China Institute of Electronic Technology National Key Laboratory of Complex Aviation System Simulation Chengdu610036 China University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798331519254

At present, most of the existing methods combine the data from different views mechanically to obtain the latent subspace with complementary information, which not only fails to make full use of the data information from specific perspectives but also brings redundancy. Therefore, we propose a novel multi-view subspace clustering method. It utilizes cycle projection to obtain a subspace construction model. At the same time, by learning the global structure and local manifold structure of this subspace while assigning learnable weights to different views, the consensus information among views and specific information from different views are captured according to the importance of different views. In this way, our method effectively reduces the original noise and redundancy, and further carries out the improvement of complementarity and consistency among views. The proposed method is optimized by using the Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM- ADM) algorithm. Experiment results on benchmark datasets confirm the effectiveness of our method. © 2024 IEEE.

关键词： Contrastive Learning

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A Region Preference-based Optimization Algorithm for Satellite Mission Planning Problem 2

A Region Preference-based Optimization Algorithm for Satelli...

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2021 2nd International Conference on Modeling, Big Data Analytics and simulation, MBDAS 2021

作者： Xiong, Minghui Xiong, Wei Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University China

For the earth observation satellite mission planning problem, objectives such as observed target quantity, observation profit, energy consumption, image quality should be considered simultaneously, which is a many-objective optimization problem. Classical optimization-based mission planning algorithms obtain a set of non-dominated solutions in the entire search space, while only a single satisfy final plan is desired by decision maker. In this paper, a five-objective optimization model for satellite mission planning problem is constructed, then a region preference-based evolutionary algorithm, HMOEA-T, is applied to obtain the desired solutions. The decision makers describe the preference on each objective in target region form, then the algorithm guides a more detailed search within the preference region rather than the entire Pareto front. Comparative studies with preference-based methods (T-NSGA-III) and classical methods (NSGA-III) are conducted. We have exemplified the proposed method manage to obtain the solutions satisfying the mission planning preference and achieve better performance in convergence and diversity. © Published under licence by IOP Publishing Ltd.

关键词： Evolutionary algorithms

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Study on photoelectric anti-interference technology of Optical Detecting system used in Surface-to-air Missiles 6

Study on photoelectric anti-interference technology of Optic...

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6th Conference on Frontiers in Optical Imaging and technology: Imaging Detection and Target Recognition

作者： Li-Qin, Zhang Lei, Chen Wei, Shen Jin-Dong, Fei Beijing Institute of Electronic System Engineering Peking100854 China Science and Technology on Special System Simulation Laboratory Peking100854 China

ISBN: (数字)9781510679733

ISBN: (纸本)9781510679726

As the battlefield environment becomes more complex, optical guided weapons will face increasingly complex photoelectric interference environment. This paper analyzes the photoelectric interference and interference mode faced by the optical detection system used in surface-to-air missiles, also gives anti-interference methods and simulation results, aiming at providing reference for anti-interference design of surface-to-air missiles. © 2024 SPIE. All rights reserved.

关键词： Surface to air missiles

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MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entity and Relation Extraction 3

MTL-JER: Meta-Transfer Learning for Low-Resource Joint Entit...

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3rd International Conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Peng, Da Pei, Zhongmin Mo, Delin Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing China Institute of War Studies Academy of Military Sciences

ISBN: (纸本)9798350335972

Joint entity and relation extraction has achieved impressive advances in NLP, such as document understanding and knowledge graph construction. The typical methods for entity and relation extraction typically break down the joint task into several smaller components or stages for ease of implementation, but this leads to a loss of the interconnected knowledge in the triple. Hence, we propose to model the triple in one module jointly. Furthermore, the labeling of a joint entity and relation extraction tasks is costly and domain-specific;therefore, it is important to improve its performance on low-resource data and domain adaption. To address this issue, we suggest using two sources that are rich in information, namely pre-trained models on large data and multi-domain text corpora. Pretraining allows us to provide the model with the fundamental ability to perform joint entity and relationship extraction. Second, through meta-learning on multi-domain text, we can improve the model's generalization capabilities, enabling it to perform well even with limited data. We present MTL-JER, a Meta-Transfer Learning method for Joint Entity and Relation Extraction in low-resource settings in this paper. Using exhaustive experiments on five datasets, we prove that our model obtains optimal results. © 2023 IEEE.

关键词： Extraction

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LEO Satellite Network Traffic Forecasting based on ARIMA-BPNN Model 3

LEO Satellite Network Traffic Forecasting based on ARIMA-BPN...

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3rd International Conference on electronic Information Engineering and Computer Communication, EIECC 2023

作者： Han, Chi Xiong, Wei Yu, Ronghuan Fu, Jingyu Space Engineering University Science and Technology on Complex Electronic System Simulation Laboratory Beijing China Jiuquan Satellite Launch Center Jiuquan China

ISBN: (纸本)9798350359961

Satellite network traffic forecasting provides key information for routing and resource allocation, which is important for the efficient operation of satellite network. However, due to the self-similarity and long-range dependence (LRD) of satellite network traffic, traditional linear or non-linear network traffic forecasting models cannot achieve sufficient forecasting accuracy. A combined model of satellite network traffic forecasting based on BPNN and ARIMA is proposed. BPNN is adopted to forecast the residuals. EMD-ARIMA and BPNN forecasting results are combined to achieve satellite network traffic forecasting. Experimental results on the satellite network traffic data generated by the ON/OFF model show that forecast accuracy of the proposed method is better than traditional model, which verifies the effectiveness of the proposed satellite network traffic forecast model. © 2023 IEEE.

关键词： BP neural network empirical mode decomposition intrinsic mode function long-range dependence satellite network

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