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15th EAI International Conference on Communications and Networking, ChinaCom 2020

作者： Du, Xiaoyu Jiang, Guoping Han, Chong Wang, Chunsong Zhou, Yi College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing China International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Zhengzhou China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9783030677190

In this paper, we propose a target Direction of Arrival (DOA) estimation algorithm through the triangular array antenna to improve the perception accuracy of intelligent vehicular millimeter-wave radar. Firstly, we utilize Total Least Square- Estimation of Signal Parameters to obtain the solution set of target azimuth with the geometrical advantages of the triangular array. Subsequently, the preliminary optimal target azimuth can be derived based on the power spectrum function of the improved Multiple Signal Classification algorithm, which is used to estimate the DOA solution set. Finally, we could estimate the optimal azimuth parameters accurately through searching the preliminary optimal target azimuth. The proposed algorithm avoids a wide range of power spectrum search, and reduces the error of azimuth estimation. Compared with both TLS-ESPRIT and MMUSIC algorithm, the spatial resolution is further improved. The evaluation results indicate that the proposed algorithm reduces the root mean square error and the computational complexity, and meanwhile improves the target azimuth estimation accuracy. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Direction of arrival

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Maximizing power saving with state transition overhead for multiple mobile subscriber stations in WiMAX

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Frontiers of Information Technology & Electronic Engineering 2016年第10期17卷 1085-1094页

作者： Bo LI Sung-kwon PARK Department of Electronic Engineering Hanyang University Seoul 133791 Korea Guangdong Provincial Key Laboratory of Big Data Analysis and Processing Sun Yat-Sen University Guangzhou 510006 China

In the IEEE 802.16e/m standard, three power saving classes （PSCs） are defined to save the energy of a mobile sub- scriber station （MSS）. However, how to set the parameters of PSCs to maximize the power saving and guarantee the quality of service is not specified in the standard. Thus, many algorithms were proposed to set the PSCs in IEEE 802.16 networks. However, most of the proposed algorithms consider only the power saving for a single MSS. In the algorithms designed for multiple MSSs, the sleep state, which is set for activation of state transition overhead power, is not considered. The PSC setting for real-time connections in multiple MSSs with consideration of the state transition overhead is studied. The problem is non-deterministic polynomial time hard （NP-hard）, and a suboptimal algorithm for the problem is proposed. Simulation results demonstrate that the energy saving of the proposed algorithm is higher than that of state-of-the-art algorithms and approaches the optimum limit.

关键词： Power saving class State transition overhead IEEE 802.16e/m Quality of service

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A Two-Step Approach for Pulse RFI Detection in SAR data

A Two-Step Approach for Pulse RFI Detection in SAR Data

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IEEE SENSORS

作者： Zongsen Lv Hengrui Zhang Ning Li Zhengwei Guo Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

The existence of pulse radio frequency interference (PRFI) severely affects the signal processing and image interpretation of synthetic aperture radar (SAR), which cannot be ignored. In SAR data processing, the detection accuracy directly affects the performance of the PRFI mitigation algorithm. However, most of the existing detectors can only detect the occurrence of PRFI, but cannot locate the PRFI. Based on a two-step process combining eigenvalue decomposition (EVD) with short-time Fourier transform (STFT), in this paper, a novel PRFI detector, which has the capability to detecting and locating PRFI, is proposed. In the proposed detector, the first step is the detection of PRFI occurrence, which is based on the Hankel structure and EVD. The second step is the location of PRFI, which is based on the STFT and a simple ratio operator. Experimental results, which are based on simulated and measured SAR data, validate the performance of the proposed PRFI detector.

关键词： Fourier transforms Signal processing algorithms Detectors Radar imaging Signal processing Time measurement Sensors

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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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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 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 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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Assisted Diagnostic Learning Based on Concept Lattice

Assisted Diagnostic Learning Based on Concept Lattice

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2021 International Conference on Signal processing and Communication Technology, SPCT 2021

作者： Shen, Xiajiong Li, Xingchen Han, Daojun Zhang, Yanfeng Henan Key Laboratory of Big Data Analysis and Processing Henan Univ. HA Kaifeng475004 China School of Computer and Information Engineering Henan Univ. HA Kaifeng475004 China Institute of Data and Knowledge Engineering Henan Univ. HA Kaifeng475004 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

With the continuous development of education, online education is becoming more and more popular with learners because of its convenience. However, online education has the problem of insufficient interaction with students. Students still need to rely on the students themselves to judge the lack of knowledge in practice tasks, which will greatly affect the learning efficiency. In this paper, we propose a method based on formal concept analysis to analyze the knowledge that may not be mastered, and a method of intensive practice for students. First of all, establishing the formal context of student error test questions, construct the concept lattice to calculate the degree of importance of the knowledge concept that may not be mastered, judge the student's mastery of the knowledge concept, and give feedback. Secondly, construct the concept lattice of the unpractised test set, and calculate the similarity of the concept extension set that meets the threshold, find similar topics and push them, and realize targeted training for students who have not mastered the knowledge concepts. © 2022 SPIE.

关键词： Students

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Research on access control decision model of Internet of Things based on attribute exploration

Research on access control decision model of Internet of Thi...

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2021 International Conference on Signal processing and Communication Technology, SPCT 2021

作者： Shen, XiaJiong Zhang, Peng Zhang, YanFeng Henan Key Laboratory of Big Data Analysis and Processing Henan Univ. HA Kaifeng475004 China School of Computer and Information Engineering Henan Univ. HA Kaifeng475004 China Institute of Data and Knowledge Engineering Henan Univ. HA Kaifeng475004 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

With the rapid development of the Internet of things, the problem of access control has become increasingly prominent. In order to solve the problems of high redundancy and low integrity caused by the traditional Role-Based Access Control model, this paper proposes an access control model of Internet of things based on attribute exploration. Firstly, the decision model is established based on attribute exploration algorithm, and finally merged into a complete decision model. The model has the function of dynamically modifying access rights in the process of building decision model. It is a new exploration in the field of access control model. © 2022 SPIE.

关键词： Internet of things

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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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