| Abstract |
Goldstein filtering is a widely used phase filtering method for Interferometric Synthetic Aperture Radar (InSAR) processing for the purpose of noise reduction. While filtering methods can effectively reduce noise, we note that strong filters may produce artifact features shown as cross-like patterns in interferograms. In this paper, the adjustable parameters of Goldstein filtering in the Sentinel Application Platform (SNAP) software are explored, and InSAR-derived DEMs were generated to investigate how each parameter influences interferograms and whether the cross-like patterns are adverse features for InSAR processing. The results showed that adaptive filter exponent and FFT size are the most influential parameters that significantly affect the strength of Goldstein filters. Furthermore, our findings imply that the presence of cross-like patterns has a negative impact on InSAR processing. As the default values for Goldstein filtering in the SNAP software are excessively high and frequently exhibits cross-like patterns, we suggest users to modify the adaptive filter exponent to a value of 0.5-0.6. |
| Authors |
Yiheng Wu   , Hsuan Ren , Austin Madson
|
| Journal Info |
Not listed | IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
|
| Publication Date |
7/16/2023 |
| ISSN |
Not listed |
Type |
article |
| Open Access |
closed
|
| DOI |
https://doi.org/10.1109/igarss52108.2023.10282000 |
| Keywords |
InSAR Technique (Score: 0.542438) , SAR Interferometry (Score: 0.5204)
|
