2023 IEEE Radar Conference (RadarConf23) 2023
DOI: 10.1109/radarconf2351548.2023.10149760
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Autofocusing of THz SAR Images by Integrating Compressed Sensing into the Backprojection Process

Abstract: The THz frequency spectrum provides an opportunity to explore high-resolution synthetic-aperture-radar (SAR) short-range imaging that can be used for various applications. However, the performance of THz SAR imaging is sensitive to phase errors that can be caused by an insuffcient amount of data samples for image formation and by path deviations that can be practically caused by SAR platform vibrations, changes in speed, changes in direction, and acceleration. To solve the former problem, an improved interpola… Show more

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(2 citation statements)
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“…Holistic post-processing, though inarguably advantageous with respect to the resolution and SNR increase afforded by the vast quantity of data, is infeasible for resource-constrained edge devices requiring low-latency, real-time operation. Among existing works, synthetic aperture radar (SAR) motion compensation typically involves the use of computationally intensive algorithms such as the Doppler Keystone transform (DKT), range cell migration correction, and phase gradient autofocus [25], [26], [27], [28], [29], [30], [31]. Other higher-performance methods such as parametric DKT [32], range envelope correction [33], short-time-Fourier-transform (STFT) histogram-based interference removal [34], range-dependent map drift correction [35], and ML algorithms [36], [37], [38], among others [25], [39], [40], [41], entail even greater computational load and/or have been exclusively deployed in post-processing.…”
Section: A Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Holistic post-processing, though inarguably advantageous with respect to the resolution and SNR increase afforded by the vast quantity of data, is infeasible for resource-constrained edge devices requiring low-latency, real-time operation. Among existing works, synthetic aperture radar (SAR) motion compensation typically involves the use of computationally intensive algorithms such as the Doppler Keystone transform (DKT), range cell migration correction, and phase gradient autofocus [25], [26], [27], [28], [29], [30], [31]. Other higher-performance methods such as parametric DKT [32], range envelope correction [33], short-time-Fourier-transform (STFT) histogram-based interference removal [34], range-dependent map drift correction [35], and ML algorithms [36], [37], [38], among others [25], [39], [40], [41], entail even greater computational load and/or have been exclusively deployed in post-processing.…”
Section: A Related Workmentioning
confidence: 99%
“…Other higher-performance methods such as parametric DKT [32], range envelope correction [33], short-time-Fourier-transform (STFT) histogram-based interference removal [34], range-dependent map drift correction [35], and ML algorithms [36], [37], [38], among others [25], [39], [40], [41], entail even greater computational load and/or have been exclusively deployed in post-processing. Such methods also tend to implement correction in the range domain only, for which typical range resolutions render mm-scale vibration correction impractical [31], [42], [43].…”
Section: A Related Workmentioning
confidence: 99%