Summed volume region selection based three-dimensional automatic target recognition for airborne LIDAR  

作　　者：Qi-shu Qian Yi-hua Hu Nan-xiang Zhao Min-le Li Fu-cai Shao 

机构地区：[1]State Key Laboratory of Pulsed Power Laser Technology,National University of Defense Technology,Hefei,230037,China [2]Anhui Province Key Laboratory of Electronic Restriction,National University of Defense Technology,Hefei,230037,China [3]The Military Representative Bureau of the Ministry of Equipment Development of the Central Military Commission in Beijing,Beijing,100191,China

出　　处：《Defence Technology（防务技术）》2020年第3期535-542,共8页Defence Technology

基　　金：This research was supported by National Natural Science Foundation of China(No.61271353,61871389);Major Funding Projects of National University of Defense Technology(No.ZK18-01-02);Foundation of State Key Laboratory of Pulsed Power Laser Technology(No.SKL2018ZR09).

摘　　要：Airborne LIDAR can flexibly obtain point cloud data with three-dimensional structural information,which can improve its effectiveness of automatic target recognition in the complex environment.Compared with 2D information,3D information performs better in separating objects and background.However,an aircraft platform can have a negative influence on LIDAR obtained data because of various flight attitudes,flight heights and atmospheric disturbances.A structure of global feature based 3D automatic target recognition method for airborne LIDAR is proposed,which is composed of offline phase and online phase.The performance of four global feature descriptors is compared.Considering the summed volume region(SVR) discrepancy in real objects,SVR selection is added into the pre-processing operations to eliminate mismatching clusters compared with the interested target.Highly reliable simulated data are obtained under various sensor’s altitudes,detection distances and atmospheric disturbances.The final experiments results show that the added step increases the recognition rate by above 2.4% and decreases the execution time by about 33%.

关 键 词：3D automatic target recognition Point cloud LIDAR AIRBORNE Global feature descriptor 

分 类 号：V243.2[航空宇航科学与技术—飞行器设计] TN958.98[电子电信—信号与信息处理]