Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging.
Saved in:
| Title: | Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging. |
|---|---|
| Authors: | Lee, In-Hyeok1 (AUTHOR), Cho, Min-Gon1 (AUTHOR), Kim, Hyun-Dong1 (AUTHOR), Kim, Kyung-Tae1 (AUTHOR) kkt@postech.ac.kr |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 9, p1369. 27p. |
| Subjects: | Compressed sensing, Synthetic aperture radar, Time-frequency analysis, High resolution imaging |
| Abstract: | Highlights: What are the main findings? A navigation-sensor-free W-band SAR imaging framework was developed to overcome the phase-wrapping limitations of conventional autofocus by integrating joint time-frequency analysis with a compressed sensing-based backprojection algorithm (CS-BPA). The proposed method successfully reconstructed focused, high-resolution SAR images from the data heavily corrupted by severe motion errors and was validated through both simulations and real-world experiments. What are the implications of the main findings? The approach enables high-quality SAR imaging on lightweight, low-cost drone platforms by eliminating the reliance on bulky and expensive navigation sensors. By iteratively reformulating the CS-BPA process and exploiting non-uniform sampling, the framework reduces the memory burden, offering a highly practical solution for W-band SAR systems. Small drone-borne W-band synthetic aperture radar (SAR) systems are highly susceptible to motion errors that conventional navigation sensors and phase-based autofocus algorithms cannot effectively resolve due to phase wrapping. This paper presents a sensor-independent imaging framework to robustly suppress these errors. First, joint time-frequency analysis is employed to identify and discard motion-corrupted pulses. Subsequently, a compressed sensing-based backprojection algorithm reconstructs high-resolution images from the remaining sparse dataset. To alleviate the substantial memory burden of matrix-based compressed sensing, the reconstruction is reformulated iteratively. Experimental results confirm that the proposed method maintains structural integrity even when up to 60% of the received pulses are corrupted and demonstrates robust focusing down to an SNR of −25 dB. This approach provides a practical, memory-efficient, and cost-effective solution for SAR platforms. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 193715400 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lee%2C+In-Hyeok%22">Lee, In-Hyeok</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cho%2C+Min-Gon%22">Cho, Min-Gon</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Hyun-Dong%22">Kim, Hyun-Dong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Kyung-Tae%22">Kim, Kyung-Tae</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> kkt@postech.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2026, Vol. 18 Issue 9, p1369. 27p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Compressed+sensing%22">Compressed sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Synthetic+aperture+radar%22">Synthetic aperture radar</searchLink><br /><searchLink fieldCode="DE" term="%22Time-frequency+analysis%22">Time-frequency analysis</searchLink><br /><searchLink fieldCode="DE" term="%22High+resolution+imaging%22">High resolution imaging</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? A navigation-sensor-free W-band SAR imaging framework was developed to overcome the phase-wrapping limitations of conventional autofocus by integrating joint time-frequency analysis with a compressed sensing-based backprojection algorithm (CS-BPA). The proposed method successfully reconstructed focused, high-resolution SAR images from the data heavily corrupted by severe motion errors and was validated through both simulations and real-world experiments. What are the implications of the main findings? The approach enables high-quality SAR imaging on lightweight, low-cost drone platforms by eliminating the reliance on bulky and expensive navigation sensors. By iteratively reformulating the CS-BPA process and exploiting non-uniform sampling, the framework reduces the memory burden, offering a highly practical solution for W-band SAR systems. Small drone-borne W-band synthetic aperture radar (SAR) systems are highly susceptible to motion errors that conventional navigation sensors and phase-based autofocus algorithms cannot effectively resolve due to phase wrapping. This paper presents a sensor-independent imaging framework to robustly suppress these errors. First, joint time-frequency analysis is employed to identify and discard motion-corrupted pulses. Subsequently, a compressed sensing-based backprojection algorithm reconstructs high-resolution images from the remaining sparse dataset. To alleviate the substantial memory burden of matrix-based compressed sensing, the reconstruction is reformulated iteratively. Experimental results confirm that the proposed method maintains structural integrity even when up to 60% of the received pulses are corrupted and demonstrates robust focusing down to an SNR of −25 dB. This approach provides a practical, memory-efficient, and cost-effective solution for SAR platforms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193715400 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18091369 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 27 StartPage: 1369 Subjects: – SubjectFull: Compressed sensing Type: general – SubjectFull: Synthetic aperture radar Type: general – SubjectFull: Time-frequency analysis Type: general – SubjectFull: High resolution imaging Type: general Titles: – TitleFull: Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lee, In-Hyeok – PersonEntity: Name: NameFull: Cho, Min-Gon – PersonEntity: Name: NameFull: Kim, Hyun-Dong – PersonEntity: Name: NameFull: Kim, Kyung-Tae IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 9 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
