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[Help]: Side lobe suppression in S-1 time series #171

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natasnat opened this issue Sep 30, 2024 · 4 comments
Open

[Help]: Side lobe suppression in S-1 time series #171

natasnat opened this issue Sep 30, 2024 · 4 comments

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@natasnat
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Hello everyone,

I’m working on PS time series processing using corner reflectors (CRs) and StaMPS for dam monitoring. However, I’ve run into an issue with side lobes in the processed images, which is affecting the accuracy of the results. I was recommended to use the pygmtsar package to tackle this issue, but I’m unsure how to implement it effectively for this specific purpose.

Does anyone have experience using pygmtsar to filter or apodize strong side lobes? Additionally, are there any available options in SNAP or StaMPS to filter or reduce these side lobes around the corner reflectors?

Thanks in advance!

@AlexeyPechnikov
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First, what are your PyGMTSAR results for the reflectors? Do you actually have such strong side lobes as in SNAP?

@natasnat
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natasnat commented Oct 5, 2024

I am not using PyGMTSAR for my analysis. I am using StaMPS software and I am trying to implement a tool or filter or something to suppress sidelobes in the StaMPS workflow. So my goal is just to implement each step to solve the problem and that is why I am asking if PyGMTSAR has such functions that I can use to implement it effectively in my StaMPS workflow.

@AlexeyPechnikov
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In this case, you would need to implement your own InSAR DEM processing, image alignment, topographic phase computation, interferogram creation, and so on—in essence, you would be building a new InSAR package similar to PyGMTSAR. Additional option to improve alignment could be splitting radar pixels into smaller sub-pixels (e.g., splitting each pixel into four) before the processing. Plus you could develop a solution for refocusing the images. But if you are considering filtering out sidelobes, this would not be a correct approach, as the issue originates in earlier processing steps.

@natasnat
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natasnat commented Oct 9, 2024

Thank you!

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