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electronic Information Engineering and Computer Communication (EIECC), International Conference on

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

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.

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Gearman Based Distributed Computation of Space Target Photometry

Gearman Based Distributed Computation of Space Target Photom...

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Informatics, Networking and Computing (ICINC), International Conference on

作者： Miao Tian Peixuan Li Wenbo Song Jieping Xu Science and Technology on Complex Electronic System Simulation laboratory Space Engineering University Beijing China

Photometry is an important optical characteristic of space targets. Due to the huge computational volume of the photometry of the full-angle of a space target, the computation time is long and is difficult to meet the realistic demand. In this study, a Gearman based distributed parallel computation framework is constructed to automatically decompose and distribute the photometry computation tasks, automatically balance the computational load, and compose the computational results. This method divides the target photometry calculation into four independent variables, conducts distributed parallel calculation respectively, and finally integrates the calculation results into single target photometry information. The distributed parallel photometry computation method based on Gearman framework is important for fast computation of full-angle photometry data of space targets and assisting space target situational awareness tasks.

关键词： Integrated optics Distributed databases Optical variables control Task analysis Informatics Photometry

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Research on Multi-Satellite Mission Planning Based on Improved Genetic Algorithm

Research on Multi-Satellite Mission Planning Based on Improv...

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Computer science and Management technology (ICCSMT), International Conference on

作者： Yang Yang Desheng Liu Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

For the multi-satellite mission planning problem, a multi-satellite mission planning model is constructed by considering the constraints of satellite’s visibility window to the target, attitude transition, storage and energy consumption, and an improved genetic algorithm is proposed to solve the model. The algorithm adopts the real number coding method to improve the solution efficiency, introduces the adaptive mechanism and the elite retention strategy, which improves the problems that the genetic algorithm is easy to fall into local optimum and converge early. The effectiveness of the improved genetic algorithm for solving multi-star mission planning is verified through simulation case analysis, and it is compared and analyzed with the standard genetic algorithm. The results show that the well genetic algorithm can achieve faster convergence and better planning results, and has better adaptability to large-scale mission planning problems.

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Exploration of the application of optimisation algorithm using stochastic gradient descent method in satellite resource allocation

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Applied Mathematics and Nonlinear sciences 2024年第1期9卷

作者： Zhao, Demin Xiong, Wei Shi, Jinjing Science and Technology on Complex Electronic System Simulation Laboratory University of Aerospace Engineering Beijing101400 China Dfh Satellite CO. Ltd Beijing100080 China North Automatic Control Technology Institute Shanxi Taiyuan030006 China

With the popularization and development of communication technology, the resource allocation problem of satellites has become a hot research topic. This study proposes a model for satellite resource allocation through the development of a beam mobilization system model and problem modeling. Then, on the basis of the linear stochastic gradient descent method, the classification accuracy of the algorithm is improved by adjusting the algorithm-solving method. Then its weight assignment method is improved to get the improved weighted linear stochastic gradient descent method. Using the optimized weighted linear stochastic gradient descent method to solve the satellite resource allocation problem from the perspective of the original problem, a model based on IWLSGD is designed and tested for performance. Through simulation experiments, the beam allocation service value of the satellite resource allocation model in this paper is 193, which is 4.32% and 3.21% higher than that of LSGD and WLSGD, respectively, and iterative convergence is faster, and its operation time and service value performs the best under different numbers of communication time slots. The system revenue, system access success rate, and system satisfaction under the interference environment between LEO and GEO are maintained at 15208, 0.8~1.0, and 85%, and keep around 7500, 1, and 75% under 5G base station interference. The satellite resource allocation model in this paper can effectively improve the utilization efficiency of communication resources and better adapt to dynamically changing interference scenarios. © 2024 Demin Zhao et al., published by Sciendo.

关键词： Resource allocation

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Depth estimation using an improved stereo network

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Frontiers of Information technology & electronic Engineering 2022年第5期23卷 777-789页

作者： Wanpeng XU Ling ZOU Lingda WU Yue QI Zhaoyong QIAN Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering UniversityBeijing 101416China Peng Cheng Laboratory Shenzhen 518055China Digital Media School Beijing Film AcademyBeijing 100088China

Self-supervised depth estimation approaches present excellent results that are comparable to those of the fully supervised approaches,by employing view synthesis between the target and reference images in the training ***,which serves as a backbone network,has some structural deficiencies when applied to downstream fields,because its original purpose was to cope with classification *** low-texture area also deteriorates the *** address these problems,we propose a set of improvements that lead to superior ***,we boost the information flow in the network and improve the ability to learn spatial structures by improving the network ***,we use a binary mask to remove the pixels in low-texture areas between the target and reference images to more accurately reconstruct the ***,we input the target and reference images randomly to expand the dataset and pre-train it on ImageNet,so that the model obtains a favorable general feature *** demonstrate state-of-the-art performance on an Eigen split of the KITTI driving dataset using stereo pairs.

关键词： Monocular depth estimation Self-supervised Image reconstruction

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Research on Radar Active Deception Jamming Identification Method Based on RESNET and Bispectrum Features 2

Research on Radar Active Deception Jamming Identification Me...

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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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Semi-supervised Open-set Recognition of Radar Active Jamming

Semi-supervised Open-set Recognition of Radar Active Jamming

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2021 CIE International Conference on Radar, Radar 2021

作者： Li, Hao Fang, Xueli Zhang, Lei Kang, Hui Zhang, Wei 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)9781665498142

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. © 2021 IEEE.

关键词： convolutional neural network open-set recognition pseudo-label Radar active jamming

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Radar Signal Detection Based on Ambiguity Function and Deep Learning 2

Radar Signal Detection Based on Ambiguity Function and Deep ...

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

作者： Lv, Fengrong Dong, Zeyu Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei 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

The ambiguity function describes the joint characteristics of the signal in the time domain and the frequency domain, and is usually used for signal recognition. The time domain and frequency domain distribution of noise is more spurious than the signal. Its ambiguity function can also reflect its characteristics. However, the direct use of the ambiguity function as the signal feature will increase the amount of calculation of the detection system, so slice it, which reduces the burden on the system for detecting signal information while preserving the information. At the same time, the radar signal detection based on neural network can avoid the influence of artificially setting the threshold on the detection performance of the system. So, we propose an algorithm for inputting the extracted fuzzy function slice sequence into a neural network to realize signal detection. simulation proves that when the signal-To-noise ratio of the received signal is very low, our proposed method still has a high detection probability. © 2021 IEEE.

关键词： Signal detection

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Radar Signal Modulation Recognition Based on Bispectrum Features and Deep learning 2

Radar Signal Modulation Recognition Based on Bispectrum Feat...

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

作者： Dong, Zeyu Lv, Fengrong Wan, Tao Jiang, Kaili Fang, Xueli Zhang, Lei 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

Signal bispectral transformation can not only suppress the influence of Gaussian white noise on signal modulation recognition, but also retain the signal amplitude and phase information. It is also used to extract the non-linear characteristics. Compared with other high-order spectra, bispectrum has a simple processing flow. However, the direct use of all bispectrum as signal features will lead to two-dimensional template matching, causing lots of calculations. Converting two-dimensional bispectrum into one-dimensional sequence, for example, extracting slice information of bispectrum, or using integral bispectrum apparently reduce the amount of data to be processed while retaining part of the bispectrum information. We input the extracted bispectral transformation of radar signals into the neural network to realize modulation recognition. The simulations validate our conclusions that our proposed methods still have a high recognition probability while SNR is low. © 2021 IEEE.

关键词： Template matching

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Operational Effectiveness Evaluation of Space-based Information system based on Improved AHP-BPNN Model 5

Operational Effectiveness Evaluation of Space-based Informat...

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5th IEEE Information technology, Networking, electronic and Automation Control Conference, ITNEC 2021

作者： Han, Chi Xiong, Wei Jian, Ping Aerospace Information Institute Aerospace Engineering University Beijing China Science and Technology on Complex Electronic System Simulation Laboratory Aerospace Engineering University Beijing China

ISBN: (纸本)9781665415989

In view of the characteristics of complex influencing factors and coupling interaction of various combat capabilities in the effectiveness evaluation of space- based information system (SIS), the effectiveness evaluation method of SIS based on improved AHP-BP neural network was proposed, which was mapped to multi-attribute decision making problem. The weight of experts was determined from the objective perspective to improve the traditional AHP and calculate the relevant influencing factors among experts. The comprehensive evaluation value is obtained according to the evaluation matrix, and the comprehensive weight of the index is obtained by the weighted average of the expert weight and the index weight. The evaluation data obtained from improved AHP and combat simulation data are used as prior samples to train BPNN to obtain the effectiveness evaluation model. Finally, sample data were obtained through MATLAB and STK co-simulation to evaluate the operational effectiveness of SIS and verify the effectiveness of the model. © 2021 IEEE.

关键词： MATLAB

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