Developing an Error Model for Ionospheric Phase Distortions in L-Band SAR and InSAR Data

Abstract:

Many of the recent and upcoming spaceborne SAR systems are operating in the L-band frequency range. The choice of L-band has a number of advantages especially for InSAR applications. These include deeper penetration into vegetation, higher coherence, and higher sensitivity to soil moisture.

While L-band SARs are undoubtedly beneficial for a number of earth science disciplines, their signals are susceptive to path delay effects in the ionosphere. Many recent publications indicate that the ionosphere can have detrimental effects on InSAR coherence and phase. It has also been shown that the magnitude of these effects strongly depends on the time of day and geographic location of the image acquisition as well as on the coincident solar activity. Hence, in order to provide realistic error estimates for geodetic measurements derived from L-band InSAR, an error model needs to be developed that is capable of describing ionospheric noise.

With this paper, we present a global ionospheric error model that is currently being developed in support of NASA’s future L-band SAR mission NISAR. The system is based on a combination of empirical data analysis and modeling input from the ionospheric model WBMOD, and is capable of predicting ionosphere-induced phase noise as a function of space and time. The error model parameterizes ionospheric noise using a power spectrum model and provides the parameters of this model in a global 1x1 degree raster. From the power law model, ionospheric errors in deformation estimates can be calculated.

In Polar Regions, our error model relies on a statistical analysis of ionospheric-phase noise in a large number of SAR data from previous L-band SAR missions such as ALOS PALSAR and JERS-1. The focus on empirical analyses is due to limitations of WBMOD in high latitude areas. Outside of the Polar Regions, the ionospheric model WBMOD is used to derive ionospheric structure parameters for as a function of solar activity. The structure parameters are converted to ionospheric phase screens from which phase power spectra are calculated.

We introduce the concept of the error model and provide examples of global error maps calculated for the NISAR mission. We also propagate ionospheric phase errors to errors in line-of-site deformation estimates assuming simple multi-temporal stacking algorithms.