Comparison of Raw Data-Based and Complex Image-Based Sparse SAR Imaging Methods

Comparison of Raw Data-Based and Complex Image-Based Sparse SAR Imaging Methods

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Sparse signal processing has already been introduced to synthetic aperture radar (SAR), which shows potential in improving imaging performance benify toyota based on raw data or a complex image.In this paper, the relationship between a raw data-based sparse SAR imaging method (RD-SIM) and a complex image-based sparse SAR imaging method (CI-SIM) is compared and analyzed in detail, which is important to select appropriate algorithms in different cases.It is found that they are equivalent when the raw data is fully sampled.Both of them can effectively suppress noise and sidelobes, and hence improve the image performance compared with a matched filtering (MF) method.

In addition, the target-to-background ratio (TBR) ultrastar dc hc570 or azimuth ambiguity-to-signal ratio (AASR) performance indicators of RD-SIM are superior to those of CI-SIM in down-sampling data-based imaging, nonuniform displace phase center sampling, and sparse SAR imaging model-based azimuth ambiguity suppression.