A GPR imaging algorithm with artifacts suppression

Zhou, Lin; Su, Yi

doi:10.1109/icgpr.2010.5550214

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…Therefore, radar image reconstruction algorithms play critical role in the GB‐SAR imaging. Synthetic aperture imaging methods are generally categorized into two classes such as back‐propagation and back‐projection methods . Back projection algorithm (BPA) has become more popular because of its near field‐wide angle SAR reconstruction ability and specific subsection selection of the region to be imaged .…”

Section: Introductionmentioning

confidence: 99%

“…Synthetic aperture imaging methods are generally categorized into two classes such as back-propagation 14-19 and back-projection methods. [20][21][22][23][24][25] Back projection algorithm (BPA) has become more popular because of its near field-wide angle SAR reconstruction ability and specific subsection selection of the region to be imaged. 12,13 If radar cross section (RCS) levels of the targets are around that of background, BPA cannot clearly display the targets signs.…”

Section: Introductionmentioning

confidence: 99%

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CFAR based morphological filter design to remove clutter from GB‐SAR images: An application to real data

Toktaş

Yiğit

Sabancı

et al. 2017

Micro & Optical Tech Letters

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Reconstructed ground based synthetic aperture radar (GB‐SAR) data generally presents high resolution images of objects on the ground. However ground and multipath reflections occurred from depression angle appear as a clutter signs in the image. Constant false alarm rate (CFAR) detector is commonly preferred threshold algorithm for removing the clutter. But there is challenge in tuning CFAR. By enlarging or shrinking the window size, the background data taken into account respectively increases or decreases, and thus the filtered image accordingly includes much clutter or less clutter with target information loss. In this study, a novel adaptive clutter removing procedure based on morphological filter (MF) is designed to compensate this tradeoff by applying after a large windowed detector. In order to test the proposed CFAR based MF (CFAR‐MF) method, two different examples of GB‐SAR experiments in which the images are reconstructed by back projection algorithm (BPA) were performed using stepped frequency continuous waveform operating. The performance of CFAR‐MF was then examined in terms of signal to clutter ratio and integrated side lobe ratio. The results show that the clutter remains of the CFAR detector are effectively cleared from the GB‐SAR image and targets were accurately detected at their true locations without any disorder.

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Section: Introductionmentioning

confidence: 99%