Open AccessAutomatic Target Recognition Technology of SAR Images Based on 2DPCA+PNN
Author(s) -
Rui-Ming Xu,
Li Dong
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1626/1/012108
Subject(s) - artificial intelligence , pattern recognition (psychology) , computer science , preprocessor , feature extraction , principal component analysis , automatic target recognition , probabilistic neural network , feature (linguistics) , computer vision , speckle noise , noise (video) , artificial neural network , synthetic aperture radar , speckle pattern , image (mathematics) , time delay neural network , linguistics , philosophy
In this paper, the SAR image in MSTAR data is used as the research object. The target recognition algorithm based on probabilistic neural network (PNN) is mainly studied. It includes three parts: SAR image preprocessing, feature extraction, classification and recognition. Lee filtering and adaptive threshold method are used to filter the speckle noise effectively, and the 2DPCA principal component analysis method is used to reduce the dimension of the image and obtain the 10 dimensional image features. The recognition part is input to the PNN training test with the acquired feature vectors, and the 85.17% correct recognition rate is obtained, and the target classification and recognition of the SAR image is completed.