典型文献
Half space object classification via incident angle based fusion of radar and infrared sensors
文献摘要：
In this paper,we introduce an incident angle based fusion method for radar and infrared sensors to improve the recognition rate of complex targets under half space scenarios,e.g.,vehicles on the ground in this paper.For radar sensors,convolutional operation is introduced into the autoencoder,a"winner-take-all(WTA)"convolutional autoencoder(CAE)is used to improve the recognition rate of the radar high resolution range profile(HRRP).Moreover,different from the free space,the HRRP in half space is more complex.In order to get closer to the real situation,the half space HRRP is simulated as the dataset.The recognition rate has a growth more than 7％com-pared with the traditional CAE or denoised sparse autoencoder(DSAE).For infrared sensor,a convolutional neural network(CNN)is used for infrared image recognition.Finally,we com-bine the two results with the Dempster-Shafer(D-S)evidence theory,and the discounting operation is introduced in the fusion to improve the recognition rate.The recognition rate after fusion has a growth more than 7％compared with a single sensor.After the discounting operation,the accuracy rate has been improved by 1.5％,which validates the effectiveness of the proposed method.
文献关键词：
中图分类号：
作者姓名：
HE Zhenyu;ZHUGE Xiaodong;WANG Junxiang;YU Shihao;XIE Yongjun;ZHAO Yuxiong
作者机构：
School of Electronic Information and Engineering,Beihang University,Beijing 100191,China;Beijing Institute of Electronic System Engineering,Beijing 100854,China;Beijing Institute of Astronautical Systems Engineering,Beijing 100076,China;Shenzhen Institute of Beihang University,Shenzhen 518038,China;School of Software,Beihang University,Beijing 100191,China
文献出处：
引用格式：
[1]HE Zhenyu;ZHUGE Xiaodong;WANG Junxiang;YU Shihao;XIE Yongjun;ZHAO Yuxiong-.Half space object classification via incident angle based fusion of radar and infrared sensors)[J].系统工程与电子技术（英文版）,2022(05):1025-1031
A类：
DSAE,discounting
B类：
Half,space,object,classification,via,incident,angle,fusion,radar,infrared,sensors,In,this,paper,we,method,recognition,rate,complex,targets,under,half,scenarios,vehicles,ground,For,convolutional,operation,introduced,into,autoencoder,winner,take,WTA,CAE,used,high,resolution,range,profile,HRRP,Moreover,different,from,free,more,order,closer,real,situation,simulated,dataset,has,growth,than,traditional,denoised,sparse,neural,network,image,Finally,bine,results,Dempster,Shafer,evidence,theory,after,compared,single,After,accuracy,been,improved,by,which,validates,effectiveness,proposed
AB值：
0.444852
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