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IEEE International Conference on Radar

作者： Jiahui Chang Qing Wang Jianhui Zhao Ning Li Henan Key Laboratory of Big Data Analysis and Processing (of Henan University) College of Computer and Information Engineering (of Henan University) Kaifeng China Air Force Research Institute Beijing China

ISBN: (纸本)9781665468893

Synthetic Aperture Radar (SAR) systems can be used for discovery and surveillance. According to the current requirements, accurate ship detection is becoming more and more important. However, the interference factors such as coherent speckle noise and strong target sidelobes will reduce the detection accuracy. In this paper, an improved two-parameter Constant False Alarm Rate (2P-CFAR) method is proposed to solve this problem. After using the non-local means (NLM) filtering method to suppress coherent speckle noise, the 2P-CFAR method is performed to obtain candidate targets, and an equal proportion segmentation procedure is carried out to optimize the aspect ratios of the candidate targets and weaken the sidelobes. Experimental results based on the SAR images acquired by the Gaofen-3 satellite verify the performance of the proposed method.

关键词： Image segmentation Satellites Filtering Spaceborne radar Surveillance Radar detection Speckle

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Research on Penetration Strategy of UAV 2020

Research on Penetration Strategy of UAV

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Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies

作者： Daojun Han Hongzhen Xiang Haolin Chen Yi Xie Institute of Data and Knowledge Engineering Henan University Kaifeng PR China School of Computer and Information Engineering Henan University Kaifeng PR China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng PR China

ISBN: (纸本)9781450387828

Taking a military operation as an example, this paper makes an in-depth study of what tactics a single UAV should adopt when facing the interception of multiple enemy UAV groups. According to the analysis of the impact diagram, the aerial range of the UAV standoff defines a threat area, that is, when the UAV arrives at the threat area, it needs to adopt a strategy for penetration, or it will be intercepted. The strategy adopted by UAV in the threat area is analyzed, and the decision control method is made.

关键词： Decision control Threat area Influence chart analysis UAV penetration

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Research on Visualization Algorithm of Association Rules Based on Concept Lattice 2020

Research on Visualization Algorithm of Association Rules Bas...

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Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies

作者： Xiajiong Shen Lijie Bao Lei Zhang Institute of Data and Knowledge Engineering Henan University Kaifeng PR China School of Computer and Information Engineering Henan University Kaifeng PR China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng PR China

ISBN: (纸本)9781450387828

The traditional association rule representation method has no way to show the essential relationship between concepts and lacks understanding of the concept level. Concept lattice is a kind of data structure which can show the relationship between concepts, concept lattice also has unique advantages in the visualization and discovery of potential knowledge of association rules. In this paper, a visualization algorithm of association rules based on concept lattice is proposed. The algorithm visually displays the association rules extracted from concept lattice. Finally, this article combines the chronic disease record data of a certain hospital to analyze and visualize the association rules. The implementation results show that the visualization method has good effects in knowledge analysis and data display.

关键词： Visualization Concept lattice Association rules Knowledge discovery

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A Metaheuristic with Learning Mechanism for Solving the Multi-school Heterogeneous School Bus Routing Problem

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2021年第4期48卷 884页

作者： Xie, Yi Kong, Yunfeng Xiang, Hongzhen Hou, Yan-e Han, Daojun Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Henan University China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475000 China Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Henan University Kaifeng475000 China College of Computer and Information Engineering Henan University Kaifeng475000 China

This paper presents a metaheuristic with online learning (MOL) to solve the multi-school heterogeneous-fleet school bus routing problem (MHSBRP). In the iterated local search (ILS) metaheuristic framework, an online learning mechanism is integrated with the neighborhood search heuristic. It evaluates the performance of search operators according to the historical search information, and then adjusts the selection probability of the operators in the following loops of search. The proposed algorithm is tested on a set of benchmark instances. The solution results show that MOL solves both mixed-load and single-load instances of MHSBRP effectively, and outperforms the ILS significantly. Compared with the algorithm without learning mechanism, MOL could improve the convergence of neighborhood search and the quality of solution. © 2021. IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Benchmarking

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Paralle acceleration of multi-mode SAR imaging on GPU 5

Paralle acceleration of multi-mode SAR imaging on GPU

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IET International Radar Conference 2020, IET IRC 2020

作者： Bai, Lan Guo, Zhengwei Wang, Kuan Fu, Zewen College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

With the continuous expansion of the application field of multi-mode synthetic aperture radar (SAR) system, which can satisfy different imaging demands. In order to get SAR image, it is necessary to image the echo received by multi-mode SAR system. However, the huge computation of the imaging algorithm affects the processing efficiency of SAR system. The power of Graphics processing Unit (GPU) can suffice the increasing demands in processing, which has been used in many common areas. The acceleration effect of GPU is very obvious compared with Central processing Unit (CPU) platform. This paper proposed a Chirp Scaling acceleration algorithm based on GPU for multi-mode SAR, and comparison of computational time over traditional CPU and GPU platform. The experimental results shows that the GPU accelerated SAR imaging algorithm can achieve a good acceleration effect. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Program processors

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A new vegetation index for cooperative inversion of winter wheat covered surface soil moisture based on sentinel-1/2 remote sensing data 5

A new vegetation index for cooperative inversion of winter w...

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IET International Radar Conference 2020, IET IRC 2020

作者： Zhang, Bei Zhao, Jianhui Li, Ning Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

Aiming at the problem of the interfere of winter wheat on radar backscattering coefficient in surface soil moisture inversion, a new vegetation index called Fusion Vegetation Index (FVI) is defined in this study. Based on the Multi-Spectral Imager (MSI) data of Sentinel-2, and the Synthetic Aperture Radar (SAR) data of Sentinel-1, using FVI to retrieve water content of winter wheat, combined with Water Cloud model, the interference of winter wheat in soil moisture inversion was reduced. The results show that good soil moisture retrieval results can be obtained by combining with FVI. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Soil moisture

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A novel cloud game framework in dual gigabit network

A novel cloud game framework in dual gigabit network

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2020 International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2020

作者： Sun, Kai Xu, Tao Shanghai Urban Construction Vocational College Shanghai201415 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China School of Computer and Information Engineering Henan University Kaifeng475004 China

With the development of 5G, cloud computing, and artificial intelligence (AI) technology, cloud game has become a hotspot about application and innovation of Gigabit bandwidth. This paper, firstly, analyses the present situation and development of cloud game to clarify the key business and key technology of cloud game, then, proposes an operational framework of cloud game, finally, the feasibility of the proposed framework is discussed and several suggestions about the operation of cloud game are given. © Published under licence by IOP Publishing Ltd.

关键词： 5G mobile communication systems

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On scattering characteristics of winter wheat at different phenological period based on Sentinel-1A SAR images 5

On scattering characteristics of winter wheat at different p...

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IET International Radar Conference 2020, IET IRC 2020

作者： Xu, Dongya Zhao, Jianhui Li, Ning College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

Phenophase period refers to the periodic natural phenomena of plants under the influence of environmental factors and human activities. In recent years, synthetic aperture radar (SAR) has been used to growth monitoring of crops. Due to complex morphological changes at different growth stage of crops, single-phase SAR data unable provide sufficient information to analyze scattering characteristics at different phenological period. In this paper, the scattering characteristics of winter wheat are studied, using time series dual-polarization Sentinel-1A SAR images. And winter wheat planting region in Kaifeng city henan province is selected as the study area. Time series C-band radar backscatter coefficient is extracted, then analyze correlation between numerical evolution and phenological change with different polarization data. The variation trend is verified by field measured data. The results show that dual-polarization SAR image is great practical significance for winter wheat phenological monitoring. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Time series

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A novel ship detection method based on Gabor feature 5

A novel ship detection method based on Gabor feature

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IET International Radar Conference 2020, IET IRC 2020

作者： Chang, Jiahui Fu, Zewen Li, Ning Chang, Jike College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Henan University Kaifeng475004 China

ISBN: (纸本)9781839535635

Synthetic Aperture Radar (SAR) Systems can be used for discovery and surveillance. According to the current requirements, accurate ship detection is becoming more and more important. However, the accuracy of traditional ship detection algorithm is not satisfying in complex scene. As a consequence, this paper proposes a novel method for detecting ships within SAR imagery using Gabor feature and Two Parameter Constant False Alarm Rate (2P-CFAR) detection technique. First, feature extraction was performed by using Gabor filter. Then, combined with the extracted orientation feature, the ship recognition of SAR image is obtained by 2P-CFAR detector. Finally, false alarms among the candidate targets were removed by geometric features of the ships. To prove the rationality of this method, experiments were carried with two high-resolution Gaofen-3 satellite SAR images in open sea background. The experimental results show that the presented method has preferable performance in the accuracy of ship identification. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Synthetic aperture radar

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Convolutional Long-Short Term Memory Network for convective weather prediction based on 3D Doppler radar data

Convolutional Long-Short Term Memory Network for convective ...

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2020 International Conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Shen, Xiajiong Meng, Kunying Guo, Zhongli Zhang, Lei Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China School of Computer and Information Engineering Henan University Kaifeng China Southwest Regional Air Traffic Management Bureau Caac Senior Engineer of Aviation Meteorology

ISBN: (纸本)9781450387828

Convectional weather is one of the weather which often occurs during the warm season, the scope of this kind of weather is normally small, short duration, etc, so it is difficult to predicted, the effects of convectional weather are very large, from the national economy to military activities will be threatened by it, so how to achieve more accurate of convection weather forecast will be of great significance. Doppler radar is one of the main tools for monitoring and early warning severe convective weather. It can provide important strong convective information for prediction. through its observed real-time echo intensity (reflectivity factor Z), radial velocity (V) and velocity spectrum width (W). Echo intensity is an important basis for judging whether severe, convective weather occurs, and radial velocity can identify wind damage and is also an important basis for judging the occurrence of severe convective weather. From the radial velocity, we can see the convergence, divergence and rotation characteristics of airflow, which are closely related to the occurrence and development of severe convective weather. Therefore, Doppler radar data plays a very important role in the detection and prediction of severe weather. At present, there are still problems about how to effectively extract these information from Doppler radar data. This paper proposes a method of near prediction based on deep learning. The neural network is used to automatically learn data features for prediction. Convolution neural network is combined with long-short-time memory network. Firstly, a three-dimensional convolution is proposed to extract the spatial features of three-dimensional original data, and then the long-short-time memory network is used to extract the features of data in time dimension, thus improving the prediction accuracy. Deep learning method avoids the process of manually extracting data features, and uses historical 3D Doppler radar image data to predict convective weather f

关键词： Long short-term memory

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