A Vehicle Target Recognition Algorithm for Wide-Angle SAR Based on Joint Feature Set Matching

被引：8
作者：
Hu, Rongchun [1 ,2 ,3 ]
Peng, Zhenming [1 ,2 ]
Ma, Juan [4 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Lab Imaging Detect & Intelligent Percept, Chengdu 610054, Sichuan, Peoples R China
[3] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Sichuan, Peoples R China
[4] Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Sichuan, Peoples R China
来源：
ELECTRONICS | 2019年 / 8卷 / 11期
基金：
中国国家自然科学基金;
关键词：
wide-angle SAR; target recognition; modulus stretch; contour thinning; feature extraction; CLASSIFICATION;
D O I：
10.3390/electronics8111252
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Target recognition is an important area in Synthetic Aperture Radar (SAR) research. Wide-angle Synthetic Aperture Radar (WSAR) has obvious advantages in target imaging resolution. This paper presents a vehicle target recognition algorithm for wide-angle SAR, which is based on joint feature set matching (JFSM). In this algorithm, firstly, the modulus stretch step is added in the imaging process of wide-angle SAR to obtain the thinned image of vehicle contour. Secondly, the gravitational-based speckle reduction algorithm is used to obtain a clearer contour image. Thirdly, the image is rotated to obtain a standard orientation image. Subsequently, the image and projection feature sets are extracted. Finally, the JFSM algorithm, which combines the image and projection sets, is used to identify the vehicle model. Experiments show that the recognition accuracy of the proposed algorithm is up to 85%. The proposed algorithm is demonstrated on the Gotcha WSAR dataset.
引用
收藏
页数：14
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