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2nd International Conference on Computer Engineering and Application, ICCEA 2021

作者： Wang, Kunteng Dong, Zeyu Wan, Tao Jiang, Kaili Xiong, Wanan Fang, Xueli University of Electronic Science Technology of China School of Electronic Science and Engineering Chengdu China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (纸本)9781665426169

In the complex electromagnetic environment of modern electronic warfare, active deception jamming poses a serious threat to radar. This paper proposes the identification of active deception jamming based on residual neural network (RESNET), and studies the bispectral characteristics of the signal and the method of identifying the active deception jamming of RESNET. This algorithm firstly extracts the bispectral features of the jamming signal, and uses the bispectral diagonal slice as the input of RSNET to realize the recognition of active deception jamming. simulation results show that the algorithm has high recognition accuracy, not only has good anti-noise performance, but also has excellent robustness under low JSR. © 2021 IEEE.

关键词： Radar

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Research on Key Technologies of Cross-domain Guidance 8

Research on Key Technologies of Cross-domain Guidance

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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Guo, Xiaoyun Wu, Chengfeng Fang, Xueli Xu, Cheng Li, Hui Beijing Institute of Mechanical and Electrical Engineering Beijing China Beijing Institute of Mechanical and Electrical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Institute of Mechanical and Electrical Engineering Key Laboratory of Complex Aviation Simulation System Beijing China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

Cross-domain synergy and intelligence will become important features of future warfare. Cross-domain guidance is one of the typical forms of cross-domain synergy. It can significantly improve the ability to respond quickly to random targets and time-sensitive targets and enhance the anti-jamming ability in the case of confrontation. This article introduces the concept and winning mechanism of cross-domain guidance, analyzes the research progress of cross-domain guidance at home and abroad, combs the key technologies of cross-domain guidance, summarizes the current challenges and problems in cross-domain guidance research, and proposes development suggestions. © 2022 SPIE

关键词： Optical engineering

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A GNSS Spoofing Detection Method based on Sparse Decomposition Technique

A GNSS Spoofing Detection Method based on Sparse Decompositi...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： He, Yuxin Zhuang, Yaqiang Zhuang, Xuebin Lin, Zijian School of System Science and Engineering Sun Yat-sen University Guangzhou China School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing Key Laboratory of Millimeter Wave and Terahertz Technology Beijing China Science and Technology On Complex Aviation Systems Simulation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

By broadcasting false Global Navigation Satellite system (GNSS) signals, spoofing attacks will induce false position and time fixes within the victim receiver. In this article, we propose a Sparse Decomposition (SD)-based spoofing detection algorithm in the acquisition process, which can be applied in a single-antenna receiver. In the first step, we map the Fast Fourier transform (FFT)-based acquisition result in a two-dimensional matrix, which is a distorted autocorrelation function when the receiver is under spoof attack. In the second step, the distorted function is decomposed into two main autocorrelation function components of different code phases. The corresponding elements of the result vector of the SD are the code-phase values of the spoofed and the authentic signals. Numerical simulation results show that the proposed method can not only outcome spoofing detection result, but provide reliable estimations of the code phase delay of the spoof attack. © 2022 IEEE.

关键词： Fast Fourier transforms

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Neural architecture search for fault diagnosis

arXiv

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arXiv 2020年

作者： Li, Xudong Hu, Yang Zheng, Jianhua Li, Mingtao National Space Science Center. CAS University of Chinese Academy of Sciences Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 mailbox Beijing China

Data-driven methods has made great progress in fault diagnosis, especially deep learning method. Deep learning is suitable for processing big data, and has a strong feature extraction ability to realize end-to-end fault diagnosis systems. Due to the complexity and variability of experimental data, some deep learning models are designed to be complex. However, designing neural network architecture requires rich professional knowledge and debugging experience, and a lot of experiments are needed to screen models and hyperparameters, increasing the difficulty of developing deep learning models. Fortunately, neural architecture search (NAS) is developing rapidly, and is becoming one of the next directions for deep learning. Given a search space, NAS can automatically search for the optimal network architecture. In this paper, we proposed a NAS method for fault diagnosis using reinforcement learning. A recurrent neural network is used as an agent to generate the network architecture. The accuracy of the generated network on the validation dataset is fed back to the agent as a reward, and the parameters of the agent are updated through the strategy gradient algorithm. In order to speed up the search process, parameters sharing method is adopted in this paper. We use PHM 2009 Data Challeng gearbox dataset to prove the effectiveness of propsed method, and obtain state-of-the-art results compared with other artificial designed network structures. To authors best knowledge, its the first time that NAS has been applied in fault diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Failure analysis

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Differentiable Neural Architecture Search for Domain Adaptation in Fault Diagnosis

SSRN

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SSRN 2023年

作者： Liu, Yumeng Li, Xudong Hu, Yang Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Jingdong Industry Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 mailbox Beijing China

In recent years, deep transfer learning has been widely applied in fault diagnosis. In particular, domain adaptation method to solve unsupervised transfer learning problem has become a research hotspot. However, these researches mainly focus on the construction of loss function, and the design of network structure still depends on manual work. A differentiable neural architecture search method is proposed to automatically search for network structures suitable for domain adaptation in fault diagnosis to solve this problem. The proposed method search for two components in the Inception search space: structures of Inception blocks and feature mask. Inception blocks are stacked to form a complete network, and the feature mask selects the features for domain adaptation. Besides, to improve the search efficiency, we search and adapt multiple target domains at the same time, expanding the application scenarios of domain adaptation. The proposed method is evaluated on two datasets, and experiments show that this method can generate networks with excellent performance. © 2023, The Authors. All rights reserved.

关键词： Failure analysis

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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

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IEEE International Conference on Radar

作者： Hao Li Xueli Fang Lei Zhang Hui Kang Wei Zhang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Key Laboratory of complex aviation simulation system Beijing China

ISBN: (纸本)9781665468893

With the emergence of various kinds of complex radar jamming, radar jamming intelligent recognition technology has increasingly become the key to electronic counter-counter measures. To achieve radar jamming open-set recognition with a small number of tagged samples, Generative adversarial network-based pseudolabeled convolutional neural network (GAN-PL-CNN) model is proposed in this paper. Firstly, radar jamming is modelled, and the radar jamming datasets with known and unknown types are established after time-frequency transformation and image processing. Then, the adaptive pseudolabeling method is used to achieve semi-supervised recognition of radar jamming by combining the learning capability of convolutional neural networks and the characteristics of pseudolabeling to increase labeled samples intelligently. Finally, generative adversarial networks are introduced to enhance the recognition ability of the model and the discrimination ability of the unknown type through the game between the generator and the discriminator in the iterative process. Experimental results show that the GAN-PL-CNN model achieves 89.7%-95.1% for known types and 30.7%-86.8% for unknown types at 3%-6% labeling rate. As the number of labeled samples increases, the recognition effect becomes better and has a greater ability to exclude unknown type.

关键词： Adaptation models Time-frequency analysis Radar measurements Neural networks Radar Radar imaging Convolutional neural networks

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

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

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International Conference on Wavelet Active Media technology and Information Processing (ICWAMTIP)

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

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

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.

关键词： Manifolds Technological innovation Clustering methods Redundancy Noise Clustering algorithms Information processing Media Minimization Similarity learning

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Large Eddy simulation of Flow and Heat Transfer Performance in Periodically Inward Corrugated Tubes

SSRN

引用

SSRN 2023年

作者： Zhong, Yuzhou Song, Yueheng Zhao, Lei Mi, Fei Zhao, Jingquan Zhu, Xiaowei School of Aeronautic Science and Engineering Beihang University Beijing100191 China Science & Technology on Complex Aviation System Simulation Laboratory Beijing100070 China Co. Ltd. Henan453049 China

Corrugated tubes are extensively unitized in enhancing heat transfer within tubular heat exchange devices. The efficiency of these corrugated tubes is closely linked to the geometric characteristics of the surface corrugations. In this study, we conducted an extensive series of Large Eddy simulations on a representative type of enhanced tube featuring periodic inward corrugations (PIC). Our goal was to compile a comprehensive and precise dataset of the thermal and hydraulic properties specific to this design. The key design parameters that define the corrugated patterns are corrugation height, corrugation width, and the length of the straight section. We systematically explored these parameters to understand their impact on heat transfer and fluid dynamics. Among these parameters, corrugation height has been identified as the most influential factor affecting flow and heat transfer properties. As the corrugation height varies from 1/8D to 3/8D, we observed a substantial increase in the friction factor and Nusselt number by a factor of 209 and 5, respectively, at Re = 1000;while the critical Reynolds number decreased roughly from 800 to 100. These findings underscore the significant role of corrugation height in shaping the flow and heat transfer performance of PIC tubes. The other two parameters, corrugation width and straight section length, were also found to be crucial in determining the overall heat transfer coefficient and pressure drop. The results of our study suggest that when utilizing this type of corrugated tubes, careful consideration is required to strike an optimal balance between heat transfer efficiency and pressure loss. The large-sets LES results presented in this paper can serve as valuable inputs for optimizing the design of PIC tubes. © 2023, The Authors. All rights reserved.

关键词： Large eddy simulation

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Model Based Management and Control of Training simulation Environment

Model Based Management and Control of Training Simulation En...

引用

Chinese Automation Congress

作者： Rongqing Meng Xingke Liu Zhichao Song Xiaogang Qiu College of Information System and Management National University of Defense Technology Science and Technology on Complex Aviation System Simulation Laboratory

ISBN: (纸本)9781467371902

Training simulation is broadly used in military training but not limited. The simulation environment contains so many elements and so many factors affect the result, so an effective and efficient mechanism to help to manage these factors is required. This article firstly listes the elements in the environment, and then builds the object models of all kinds of objects. Based on these object models, the experiment frame is designed. Finally, a simple case study is given. According to the actual application, these models and frame facilitate the experiment management and help the analysts to analyze the simulation result.

关键词： Training simulation Model Based Management and Control of simulation

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Adaptive radar detection of subspace-based distributed target in power heterogeneous clutter

arXiv

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arXiv 2024年

作者： Xiao, Daipeng Liu, Weijian Liu, Jun Dai, Lingyan Fang, Xueli Ge, Jianjun Wuhan Electronic Information Institute Wuhan430019 China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230027 China Key Laboratory of Complex Aviation Simulation System Beijing100076 China Information Science Academy China Electronics Technology Group Corporation Beijing100041 China

This paper investigates the problem of adaptive detection of distributed targets in power heterogeneous clutter. In the considered scenario, all the data share the identical structure of clutter covariance matrix, but with varying and unknown power mismatches. To address this problem, we iteratively estimate all the unknowns, including the coordinate matrix of the target, the clutter covariance matrix, and the corresponding power mismatches, and propose three detectors based on the generalized likelihood ratio test (GLRT), Rao and the Wald tests. The results from simulated and real data both illustrate that the detectors based on GLRT and Rao test have higher probabilities of detection (PDs) than the existing competitors. Among them, the Rao test-based detector exhibits the best overall detection performance. We also analyze the impact of the target extended dimensions, the signal subspace dimensions, and the number of training samples on the detection performance. Furthermore, simulation experiments also demonstrate that the proposed detectors have a constant false alarm rate (CFAR) property for the structure of clutter covariance matrix. © 2024, CC BY.

关键词： Radar clutter

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