Closed AmazingSAR closed 8 months ago
The error message could be better, but I'd guess that what's happening is you're processing data from ALOS that's been packed in a NISAR-like raw data format. It's trying to read SweepSAR parameters from the raw data and not finding them. To work around this issue you can disable elevation antenna pattern correction by setting eap: false
in the runconfig, e.g.,
runconfig:
groups:
processing:
is_enabled:
eap: false
I disabled elevation antenna pattern correction in the runconfig. The focus workflow works fine. But the result seems wrong.
Input:
amazingsar@geekpro-17irb:~/data1$ python3 ~/install/isce3.3/packages/nisar/workflows/focus.py rslc_config.yaml
Output:
Input:
amazingsar@geekpro-17irb:~/data1$ gdal_translate -of ENVI HDF5:"rslc.h5"://science/LSAR/RSLC/swaths/frequencyA/HH HH.slc
Output:
Input file size is 6488, 26388
0...10...20...30...40...50...60...70...80...90...100 - done.
Run python script from SDS-on-command
Output:
Are there any example config file for the official example data set?
First, SLC amplitudes tend to have a large dynamic range, so we usually view the images on a log scale (or some other nonlinear color scale). So instead you might try
power_db = 20 * np.log10(np.abs(slc))
plt.imshow(power_db, cmap="gray")
You may need to add some vmin
and vmax
parameters to imshow
to get a satisfactory plot. I usually plot a dynamic range of 40 dB or so.
Second, depending on what version of isce3 you're running, the pixel values may be stored using 16-bit floating point. In that case you need to have the values at least roughly calibrated or you risk losing precision. I notice in your config file you have encoding_scale_factor: 1e-08
and then in the log I see the stats reports SLC values of similarly small magnitude. While you could supply a separate calibration file, for your purposes it's probably simpler to just change encoding_scale_factor: 1.0
to get more reasonable values.
@bhawkins-jpl Thanks a lot for your reply! The result seems reasonable now except artificial traces in dark areas such as lakes. The results are displayed as follows: full area lake area The artificial traces along horizontal parallel to radar range direction. Are these artificial traces related to the absence of EAP processing? And how can I do to remove it?
Those artifacts are due to radio frequency interference (RFI). Removing RFI is an ongoing research topic. There's already an algorithm the code, but it's not enabled by default. You could try setting mitigation_enabled: true
in your config file (example) and see if that improves the image.
@bhawkins-jpl Thanks again, I have tried setting mitigation_enabled: true option in my config file.
The RFI removing algorithm works but the task is too difficult.
@bhawkins-jpl Many thanks for your kind and warm help.
When testing NISAR Sample Data Product with ISCE3, KeyError occurred in "~/isce3/packages/nisar/products/readers/Raw/Raw.py" line 603.
Here is my rslc_config.yaml.
Does anyone know what happened here?