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Updated: Jan 13, 2026

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Novel Amplitude-Based Approach for Reducing Sidelobes in Persistent Scatterer Interferometry Processing Using

Natascha Liedel1, Jonas Ziemer1, Jannik Jänichen1

  • 1Department for Earth Observation, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

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Summary
This summary is machine-generated.

This study presents an amplitude-based Spatially Variant Apodization (SVA) filter to reduce Synthetic Aperture Radar (SAR) sidelobes. The method preserves interferometric phase, enhancing Persistent Scatterer Interferometry (PSI) for accurate dam deformation monitoring.

Keywords:
PSIS-1SARSNAP2StaMPSSVAStaMPSactive reflectoramplitude-based filteringdam monitoringsidelobes

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Area of Science:

  • Remote Sensing
  • Geophysics

Background:

  • Synthetic Aperture Radar (SAR) data often suffers from sidelobe artifacts, which can degrade the accuracy of deformation monitoring.
  • Persistent Scatterer Interferometry (PSI) is a valuable technique for measuring ground deformation, but it is sensitive to amplitude variations and phase distortions.

Purpose of the Study:

  • To introduce and evaluate an amplitude-based Spatially Variant Apodization (SVA) method for reducing sidelobes in SAR data.
  • To integrate the SVA filter into the Sentinel Application Platform to Stanford Method for Persistent Scatterers (SNAP2StaMPS) workflow for dam monitoring.
  • To assess the impact of SVA filtering on Persistent Scatterer (PS) detection and deformation measurement accuracy.

Main Methods:

  • An amplitude-based SVA filter was developed and applied to the In-phase (I) and Quadrature (Q) components of coregistered SAR data.
  • The SVA filter was implemented using SNAP-Python (snappy) within the SNAP2StaMPS workflow.
  • The method was tested on Sentinel-1 data from the Sorpe Dam, Germany, focusing on sidelobe reduction and phase preservation.

Main Results:

  • SVA filtering successfully reduced sidelobe artifacts in SAR data, leading to a 39.26% decrease in sidelobe-affected Persistent Scatterers (PS).
  • The amplitude-based approach preserved the original interferometric phase, ensuring accurate deformation values with a Root Mean Square Error (RMSE) of approximately 0.38 mm.
  • The integration of SVA filtering into the SNAP2StaMPS workflow improved PS detection and dam deformation monitoring capabilities.

Conclusions:

  • The novel amplitude-based SVA method effectively reduces sidelobes in SAR data while preserving crucial phase information.
  • This approach enhances the accuracy and reliability of PSI for dam deformation monitoring, particularly in the presence of strong sidelobes.
  • The developed SVA filter extends the SNAP2StaMPS workflow, offering a valuable tool for geoscientific applications requiring precise SAR interferometry.