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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

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Published on: August 12, 2013

Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation.

Qingqing Feng¹, Huaping Xu², Zhefeng Wu³

¹School of Electronic and Information Engineering, Beihang University, Beijing 100191, China. 18010127731@163.com.

Sensors (Basel, Switzerland)

|November 26, 2016

Summary

This summary is machine-generated.

This study introduces an improved Goldstein interferogram filter to reduce phase noise in Interferometric SAR (InSAR) data. The enhanced filter effectively suppresses noise while preserving crucial fringe details for accurate geophysical measurements.

Keywords:

Goldstein interferogram filter interferometric synthetic aperture radar (InSAR)local fringe frequency estimation

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Area of Science:

Geophysics
Remote Sensing
Signal Processing

Background:

Interferometric SAR (InSAR) data quality is crucial for geophysical measurements like height and displacement.
Phase noise in interferograms significantly impacts subsequent processing steps, including phase unwrapping.
Effective phase filtering is essential for accurate InSAR data analysis.

Purpose of the Study:

To propose an improved Goldstein interferogram filter for enhanced phase noise suppression.
To preserve fringe edges and signal integrity during the InSAR filtering process.
To improve the accuracy of InSAR-derived geophysical measurements.

Main Methods:

An adaptive filter step was introduced before frequency estimation to enhance accuracy.
Fringe frequency was estimated and removed from noisy phase data to preserve characteristics.
A modified Goldstein filter with adaptive parameter (alpha) was applied to the residual phase.
Filtered residual phase was combined with removed fringe frequency for the final interferogram.

Main Results:

The proposed method effectively suppresses phase noise in interferograms.
Fringe edges and signal characteristics are well-preserved.
Experimental results with simulated and real data validate the filter's effectiveness.
Minimized signal loss alongside noise reduction was achieved.

Conclusions:

The improved Goldstein filter offers superior performance in InSAR phase filtering.
The method enhances the quality of interferograms for reliable geophysical analysis.
This technique minimizes noise while preserving essential signal features in InSAR data.