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An InSAR Ionospheric Correction Method Based on Variance Component Estimation With Integration of MAI and RSS Measurements
- Source :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 1423-1433 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- Ionospheric phase delay can seriously affect the low-frequency spaceborne synthetic aperture radar (SAR) systems. Ionospheric correction is, therefore, vital to improving the measurement accuracy of Interferometric SAR (InSAR). InSAR ionospheric correction relies mainly on two kinds of approaches, i.e., one uses SAR azimuth offsets measures, and the other achieves through a range split-spectrum (RSS) technique. However, the two approaches have different spatial sensitivities to the ionosphere, but they can complement each other. In this study, we present an integration InSAR ionospheric correction method. This method uses the Helmert variance component estimation to reasonably allocate the weights for the ionospheric measurements obtained from the azimuth offset-based and RSS techniques to improve the ionospheric correction performance. The azimuth offset can be derived from a pixel offset-tracking procedure or multiple-aperture InSAR. We demonstrated the proposed method on 28-MHz FBS mode ALOS-1 PALSAR images acquired before and after the Wenchuan earthquake in Sichuan Province, China, 2008. This study also applied the proposed method to 14-MHz FBD mode ALOS-1 PALSAR images with no significant surface deformation and high coherence in Chile. After the ionospheric correction with the proposed method, we found that the ionospheric errors in the Wenchuan and Chile cases have varied from -31.0 to 21.1 cm and -4.7 to 93.9 cm, respectively. The results show that the proposed method can effectively remove the long-wavelength ionospheric delay. Our study reveals that this method can also alleviate the influence of local ionospheric disturbance simultaneously.
Details
- Language :
- English
- ISSN :
- 21511535
- Volume :
- 14
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.120b9a86b44f48dcb54731d1a1edb33b
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/JSTARS.2020.3045267