Batch Processing for Enhanced InISAR Imaging of Space Targets

High-precision 3-D reconstruction of satellites is critical for automatic target recognition (ATR). This article introduces a batch processing-based method to enhance the performance of interferometric inverse synthetic aperture radar (InISAR) imaging. By utilizing the phase information within the i...

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Vydané v:IEEE transactions on geoscience and remote sensing Ročník 62; s. 1 - 15
Hlavní autori: Qian, Wenshuo, Wang, Junling, Zhao, Lizhi, Li, Haiguang, Tang, Fujie
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Automatic target recognition
Batch processing
Batch production systems
Estimation
Height
Image enhancement
Image reconstruction
Imaging
Information processing
interferometric inverse synthetic aperture radar (InISAR)
Inverse synthetic aperture radar
inverse synthetic aperture radar (ISAR) image sequence
Orbits
Performance enhancement
Phase unwrapping
Radar
Radar imaging
SAR (radar)
Satellite imagery
Satellites
space target
Space vehicles
Spaceborne radar
Three-dimensional displays
ISSN:0196-2892, 1558-0644
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Abstract High-precision 3-D reconstruction of satellites is critical for automatic target recognition (ATR). This article introduces a batch processing-based method to enhance the performance of interferometric inverse synthetic aperture radar (InISAR) imaging. By utilizing the phase information within the inverse synthetic aperture radar (ISAR) image sequence, the main error components of height estimation are accurately estimated via the ordinary least squares (OLSs) method. In addition, an arc interval determination strategy for optimizing the batch processing performance is proposed. To ensure accurate phase unwrapping in challenging imaging scenarios, a phase unwrapping method based on the minimum standard deviation criterion is also proposed. Simulation experiments validate the effectiveness and superiority of the proposed algorithms. Compared with the traditional two-ISAR-image InISAR imaging method, the batch processing approach improves the precision of height estimation by approximately 50% with an arc length of approximately 15°.
AbstractList High-precision 3-D reconstruction of satellites is critical for automatic target recognition (ATR). This article introduces a batch processing-based method to enhance the performance of interferometric inverse synthetic aperture radar (InISAR) imaging. By utilizing the phase information within the inverse synthetic aperture radar (ISAR) image sequence, the main error components of height estimation are accurately estimated via the ordinary least squares (OLSs) method. In addition, an arc interval determination strategy for optimizing the batch processing performance is proposed. To ensure accurate phase unwrapping in challenging imaging scenarios, a phase unwrapping method based on the minimum standard deviation criterion is also proposed. Simulation experiments validate the effectiveness and superiority of the proposed algorithms. Compared with the traditional two-ISAR-image InISAR imaging method, the batch processing approach improves the precision of height estimation by approximately 50% with an arc length of approximately 15°.
Author Tang, Fujie
Qian, Wenshuo
Li, Haiguang
Zhao, Lizhi
Wang, Junling
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Snippet High-precision 3-D reconstruction of satellites is critical for automatic target recognition (ATR). This article introduces a batch processing-based method to...
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SubjectTerms Algorithms
Automatic target recognition
Batch processing
Batch production systems
Estimation
Height
Image enhancement
Image reconstruction
Imaging
Information processing
interferometric inverse synthetic aperture radar (InISAR)
Inverse synthetic aperture radar
inverse synthetic aperture radar (ISAR) image sequence
Orbits
Performance enhancement
Phase unwrapping
Radar
Radar imaging
SAR (radar)
Satellite imagery
Satellites
space target
Space vehicles
Spaceborne radar
Three-dimensional displays
Title Batch Processing for Enhanced InISAR Imaging of Space Targets
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