国家自然科学基金(61071139)

作品数：9被引量：38H指数：4
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相关作者：许喆平邓小乐郎荣玲更多>>
相关机构：北京航空航天大学更多>>
相关期刊：《Chinese Journal of Electronics》《航空学报》《Chinese Journal of Aeronautics》更多>>
相关主题：RADARSYNTHETICSAR_IMAGESAPERTURETARGETS更多>>
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A novel visual attention method for target detection from SAR images被引量：5
《Chinese Journal of Aeronautics》2019年第8期1946-1958,共13页Fei GAO Aidong LIU Kai LIU Erfu YANG Amir HUSSAIN 
supported by the National Natural Science Foundation of China(Nos.61771027,61071139,61471019,61671035);supported in part under the Royal Society of Edinburgh-National Natural Science Foundation of China(RSE-NNSFC)Joint Project(2017–2019)(No.6161101383)with China University of Petroleum(Huadong);partially supported by the UK Engineering and Physical Sciences Research Council(EPSRC)(Nos.EP/I009310/1,EP/M026981/1)
Synthetic Aperture Radar(SAR) imaging systems have been widely used in civil and military fields due to their all-weather and all-day abilities and various other advantages. However, due to image data exponentially in...
关键词：Learning strategy SYNTHETIC APERTURE Radar(SAR) images Target detection TOP-DOWN Visual ATTENTION mechanism 
CNN Based Classification of Rigid Targets in Space Using Radar Micro-Doppler Signatures被引量：5
《Chinese Journal of Electronics》2019年第4期856-862,共7页WANG Jun ZHU He LEI Peng ZHENG Tong GAO Fei 
supported by the National Natural Science Foundation of China(No.61501011,No.61671035,No.61771027,No.61071139)
Micro-motion characteristics play an important role in some applications of radar target classification.In this paper,a classification method of rigid targets in space using radar micro-Doppler signatures is proposed....
关键词：INERTIAL model MICRO-MOTION RADAR MICRO-DOPPLER Convolutional neural network 
A Novel Separability Objective Function in CNN for Feature Extraction of SAR Images被引量：4
《Chinese Journal of Electronics》2019年第2期423-429,共7页GAO Fei WANG Meng WANG Jun YANG Erfu ZHOU Huiyu 
funded by the National Natural Science Foundation of China(No.61771027,No.61071139,No.61471019,No.61501011,No.61171122);supported in part under the RSE-NNSFC Joint Project(2017-2019)(No.6161101383)with China University of Petroleum(Huadong);supported by Invest NI/Philips,UK EPSRC(No.EP/N011074/1);Royal Society-Newton Advanced Fellowship(No.NA160342)
Convolutional neural network(CNN) has become a promising method for Synthetic aperture radar(SAR) target recognition. Existing CNN models aim at seeking the best separation between classes, but rarely care about the s...
关键词：SYNTHETIC APERTURE radar(SAR) CONVOLUTION neural network(CNN) Classification Linear SEPARABILITY Objective function 
Hierarchical Feature-Based Detection Method for SAR Targets Under Complex Environment被引量：4
《Chinese Journal of Electronics》2017年第3期647-653,共7页GAO Fei MA Fei LUO Xiling WANG Jun SUN Jinping 
supported by the National Natural Science Foundation of China(No.61071139,No.61471019,No.61671035);the Aeronautical Science Foundation of China(No.20142051022);the Foundation of ATR Key Lab
A reliable target detection method for Synthetic aperture radar(SAR)images is needed urgently with the wide application of SAR systems.The performance of conventional detection algorithms,such as Constant false alarm ...
关键词：Synthetic aperture radar(SAR) Targets detection Human visual system(HVS) Complex background Hierarchical model and X(HMAX) 
Fast Algorithm for Inverse Two-Dimensional S Transform and Its Application in Time-Frequency Filtering for SAR Image Despeckling被引量：1
《Chinese Journal of Electronics》2016年第1期100-105,共6页GAO Fei ZHANG Ye WANG Jun SUN Jinping 
supported by the National Natural Science Foundation of China(No.61071139,No.61171122,No.61471019,No.61501011);the Aeronautical Science Foundation of China(No.20142051022);the Pre-research Project(No.9140A07040515HK01009)
S transform is a time-frequency representation which has been applied in various fields, yet suffers the problem of time and resource consumption. In order to overcome this problem and facilitate its application in im...
关键词：Time-frequency representation Fast al-gorithm Two-dimensional S transform Time-frequencyfilter Synthetic aperture radar （SAR） image Speckle noisereduction. 
A Novel Refined Track Initiation Algorithm for Group Targets Based on Group Model被引量：3
《Chinese Journal of Electronics》2014年第4期851-856,共6页GAO Fei REN He WANG Jun Amir Hussain Tariq S. Durrani 
supported by the National Natural Science Foundation of China(No.61071139,No.60702011);the Foundation of ATR Key Lab,the Fundamental Research Funds for the Central Universities,"New Star in Blue Sky"Program Foundation,and the Royal Society of Edinburgh(RSE);the National Natural Science Foundation of China(NNSFC)under the RSE-NNSFC Joint Project(2012–2014)(No.61211130309)with the University of Stirling,Scotland,SK
Traditional refined track initiation methods for group targets have mistakes or loss of tracks when tracking irregular motions, for the reason that they rely on a stable relative position of group members. To solve th...
关键词：Group targets Track initiation Group model State equation Data association. 
飞机性能参数预测的不确定性处理被引量：11
《航空学报》2012年第6期1100-1107,共8页许喆平 郎荣玲 邓小乐 
国家自然科学基金(61071139);国家"863"计划(SQ2010AA1101356002)~~
利用飞机的性能参数对飞机进行故障预报和状态监控是非常重要的。飞机的性能参数不仅具有非线性而且往往包含噪声,使得故障预测结果具有不确定性。针对这些问题,研究了利用非线性支持向量机处理飞机性能参数的预测问题,通过增加线性约...
关键词：飞机性能参数 预测 支持向量机 不确定性 排气温度 排气温度裕度 
An Adaptive Fuzzy Markov Random Field Model for Change Detection被引量：1
《Chinese Journal of Electronics》2012年第3期466-470,共5页GAO Fei CHEN Bona SUN Jinping 
Manuscript Received Apr. 2011; Accepted Nov. 2011. This work is supported by the National Natural Science Foundation of China （No.61071139, No.60702011）, the Fundamental Research Funds for the Central Universities and ＂New Star in Blue Sky＂ Program Foundation.
This paper proposes a change detection al- gorithm based on a novel adaptive fuzzy Markov random field model. The purpose is to improve the adaptability and accuracy of change detection algorithm through a non- parame...
关键词：Fuzzy Markov random field Gradientprojection optimization method Change detection. 
The Heuristic Algorithms for Selecting the Parameters of Support Vector Machine for Classification被引量：4
《Chinese Journal of Electronics》2012年第3期485-488,共4页LANG Rongling DENG Xiaole GAO Fei 
Manuscript Received Apr. 2011; Accepted May 2011. This work is supported by the National Natural Science Foundation of China （No.60702011, No.61071139）, the WeiShi Foundation （YWF-11-03-Q-007） and ＂New Star in Blue Sky＂ Program Foundation.
The performance of Gaussian kernel Sup- port vector machine （SVM） for classification is determined by scale parameter of Gaussian kernel function and error penalty parameter C. A heuristic approach is proposed to t...
关键词：Support vector machine （SVM） Param-eters selection Classification. 
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