Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging.
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| Title: | Efficient Compressed Sensing-Based Backprojection Approach for Small Drone-Borne W-Band SAR Imaging. |
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| 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] |
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| Database: | Engineering Source |
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| 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] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18091369 |
