Toward Operational Compensation of Ionospheric Effects in SAR Interferograms: The Split-Spectrum Method

The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor.

[1]  Sailes K. Sengijpta Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[2]  Franz J. Meyer,et al.  A review of ionospheric effects in low-frequency SAR — Signals, correction methods, and performance requirements , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[3]  Marcello de Michele,et al.  Assessing Ionospheric Influence on L-Band SAR Data: Implications on Coseismic Displacement Measurements of the 2008 Sichuan Earthquake , 2010, IEEE Geoscience and Remote Sensing Letters.

[4]  M. Seymour,et al.  Maximum likelihood estimation for SAR interferometry , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[5]  D. P. Belcher,et al.  Theoretical limits on SAR imposed by the ionosphere , 2008 .

[6]  Benjamin Friedlander,et al.  On the Cramer-Rao bound for time delay and Doppler estimation , 1984, IEEE Trans. Inf. Theory.

[7]  Konstantinos Papathanassiou,et al.  Correction of ionospheric distortions in low frequency interferometric SAR data , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[8]  F. Rocca,et al.  Recovering time and space varying phase screens through SAR multi-squint differential interferometry , 2012 .

[9]  Joong-Sun Won,et al.  Ionospheric Correction of SAR Interferograms by Multiple-Aperture Interferometry , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Marc Rodriguez-Cassola,et al.  On the Dependence of Delta-k Efficiency on Multilooking , 2015, IEEE Geoscience and Remote Sensing Letters.

[11]  Michael Eineder,et al.  High-resolution estimation of ionospheric phase screens through semi-focusing processing , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[12]  Sassan Saatchi,et al.  On the detection of Faraday rotation in linearly polarized L-band SAR backscatter signatures , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Henriette Sudhaus,et al.  Strain partitioning at the eastern Pamir-Alai revealed through SAR data analysis of the 2008 Nura earthquake , 2014 .

[14]  Franz J. Meyer,et al.  The Potential of Low-Frequency SAR Systems for Mapping Ionospheric TEC Distributions , 2006, IEEE Geoscience and Remote Sensing Letters.

[15]  Franz J. Meyer,et al.  Prediction, Detection, and Correction of Faraday Rotation in Full-Polarimetric L-Band SAR Data , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[16]  Michael Eineder,et al.  Interferometric absolute phase determination with TerraSAR-X wideband SAR data , 2009, 2009 IEEE Radar Conference.

[17]  Franz J. Meyer,et al.  Estimation and compensation of ionospheric delay for SAR interferometry , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[18]  R. Hanssen Radar Interferometry: Data Interpretation and Error Analysis , 2001 .

[19]  P. Rosen,et al.  Measurement and mitigation of the ionosphere in L-band Interferometric SAR data , 2010, 2010 IEEE Radar Conference.

[20]  Volker Wilken,et al.  Total electron content models and their use in ionosphere monitoring , 2010 .

[21]  Zhensen Wu,et al.  A survey of ionospheric effects on space-based radar , 2004 .

[22]  Jun Su Kim,et al.  Tropospheric and Ionospheric Effects in Spaceborne Single-Pass SAR Interferometry and Radargrammetry , 2014 .

[23]  Franz J. Meyer,et al.  Performance Requirements for Ionospheric Correction of Low-Frequency SAR Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Peizhen Zhang,et al.  Slip maxima at fault junctions and rupturing of barriers during the 2008 Wenchuan earthquake , 2009 .

[25]  Anthony Freeman,et al.  Calibration of linearly polarized polarimetric SAR data subject to Faraday rotation , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[26]  Fabio Rocca,et al.  The wavenumber shift in SAR interferometry , 1994, IEEE Trans. Geosci. Remote. Sens..

[27]  Michael Eineder,et al.  Accuracy of differential shift estimation by correlation and split-bandwidth interferometry for wideband and delta-k SAR systems , 2005, IEEE Geoscience and Remote Sensing Letters.

[28]  Francesco De Zan Coherent Shift Estimation for Stacks of SAR Images , 2011, IEEE Geoscience and Remote Sensing Letters.