Title | ||
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Space Target Attitude Estimation From Isar Image Sequences With Key Point Extraction Network |
Abstract | ||
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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. |
Year | DOI | Venue |
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2021 | 10.1109/LSP.2021.3075606 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | DocType | Volume |
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 | Journal | 28 |
ISSN | Citations | PageRank |
1070-9908 | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Pengfei Xie | 1 | 0 | 0.68 |
Lei Zhang | 2 | 195 | 22.87 |
Chuan Du | 3 | 0 | 2.70 |
Xiaoqing Wang | 4 | 14 | 4.24 |
Weijun Zhong | 5 | 0 | 0.34 |