Space Target Attitude Estimation From ISAR Image Sequences With Key Point Extraction Network

被引:15
|
作者
Xie, Pengfei [1 ]
Zhang, Lei [1 ]
Du, Chuan [1 ]
Wang, Xiaoqing [1 ]
Zhong, Weijun [2 ]
机构
[1] Sun Yat Sen Univ, Sch Elect & Commun Engn, Shenzhen 518107, Peoples R China
[2] State Key Lab Astronaut Dynam, Xian 710043, Peoples R China
基金
中国国家自然科学基金;
关键词
Feature extraction; Space vehicles; Estimation; Imaging; Geometry; Position measurement; Three-dimensional displays; ISAR image sequence; convolutional neural network(CNN); space target; key points extraction; attitude estimation;
D O I
10.1109/LSP.2021.3075606
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Attitude determination of space target from an inverse synthetic aperture radar (ISAR) image sequence is an important but difficult task, because of the complex electromagnetic scattering characteristics of the target. To autonomously estimate the attitude of the space target from the ISAR image sequence, this letter introduces the key point feature extraction network (KPEN), and proposes a novel method for attitude determination via the key point feature extraction. The geometric relationship between the target attitude parameters and the key point feature is established through range-Doppler (RD) projection matrix. With the help of the key point extraction network, key point feature is extracted from ISAR image. Then the target attitude and its component size are autonomously recovered through key point feature by solving a nonlinear optimization. Extensive experiments show the effectiveness and superiority of the proposal.
引用
收藏
页码:1041 / 1045
页数:5
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