Translational Motion Compensation of Space Micromotion Targets Using Regression Network Article Swipe
Yizhe Wang
,
Cunqian Feng
,
Yongshun Zhang
,
Sisan He
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2947277
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2947277
The high-speed translational motion of space targets will cause the micro-Doppler to shift, tilt, and fold, which brings great difficulty to the extraction of micromotion features. Translational motion must be compensated in advance to extract the authentic characteristics of micro-Doppler curves. To solve the problem of translational motion compensation, an estimation method of translational parameters based on deep learning theory is proposed. A polynomial model describing translational motion is constructed firstly by analyzing its dynamic principle. Meanwhile, the parametric characterization of micromotion signal is deduced by taking the cone target as an example. On this basis, two regression networks that can estimate acceleration and velocity respectively from the time-frequency graph are built using transfer learning. The translational motion compensation is accomplished with high accuracy and low computation complexity. The proposed method can also achieve satisfactory results in the presence of high intensity noise and discontinuous scattering points. Finally, the effectiveness and robustness of the proposed method are validated by simulations.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2019.2947277
- https://ieeexplore.ieee.org/ielx7/6287639/8600701/08868085.pdf
- OA Status
- gold
- Cited By
- 8
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2981256085
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2981256085Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2019.2947277Digital Object Identifier
- Title
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Translational Motion Compensation of Space Micromotion Targets Using Regression NetworkWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-01-01Full publication date if available
- Authors
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Yizhe Wang, Cunqian Feng, Yongshun Zhang, Sisan HeList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2019.2947277Publisher landing page
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https://ieeexplore.ieee.org/ielx7/6287639/8600701/08868085.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6287639/8600701/08868085.pdfDirect OA link when available
- Concepts
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Computer science, Translational motion, Robustness (evolution), Parametric statistics, Motion compensation, Artificial intelligence, Computer vision, Computation, Control theory (sociology), Algorithm, Mathematics, Physics, Chemistry, Biochemistry, Gene, Statistics, Classical mechanics, Control (management)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
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2024: 1, 2022: 2, 2021: 4, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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24Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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| primary_location.pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/8600701/08868085.pdf |
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| publication_date | 2019-01-01 |
| publication_year | 2019 |
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