Abstract
To derive surface displacement, interferometric stacking with synthetic aperture radar (SAR) data is commonly used, and this technique is now in the implementation phase in the real world. Persistent scatterer interferometry (PSI) is one of the most universal approaches among in- terferometric stacking techniques, and non-linear non-parametric PSI (NN-PSI) was proposed to overcome the drawbacks of PSI approaches. The estimation of the non-linear displacements was successfully conducted using NN-PSI. However, the estimation of NN-PSI is not always stable with certain displacements because wider range of the velocity spectrum is used in NN-PSI than the conventional approaches; therefore, a calculation procedure and parameter optimization are needed to consider. In this paper, optimized parameters and procedures of NN-PSI are proposed, and real data processing with Sentinel-1 in the Kanto region in Japan was conducted. We confirmed that the displacement estimation was comparable to the measurement of the permanent global positioning system (GPS) stations, and the root mean square error between the GPS measurement and NN-PSI estimation was less than 3 mm in two years. The displacement over 2 ambiguity, which the conventional PSI approach wrongly reconstructed, was also quantitatively validated and successfully estimated by NN-PSI. As a result of the real data processing, periodical displacements were also reconstructed through NN-PSI. We concluded that the NN-PSI approach with the proposed parameters and method enabled the estimation of several types of surface displacements that conventional PSI approaches could not reconstruct.
Highlights
In the past decade, the number of operative spaceborne synthetic aperture radar (SAR) sensors has increased dramatically
It is clear that the step displacements with less than one quarter of the wavelength can be reconstructed by NN-persistent scatterer interferometry (PSI) as well as by conventional PSI (ConvPSI)
The reconstructed displacement close by the Pt1 and Pt2 shown in Figure 9 are investigated and compared with the displacement measured at GNSS Earth Observation Network System (GEONET)
Summary
The number of operative spaceborne synthetic aperture radar (SAR) sensors has increased dramatically. In this circumstance, the use of multi-temporal images is essential, and one of the techniques to monitor surface displacements with SAR data processing is called interferometric stacking [1]. One of the significant limitations in the PSI technique is in estimating non-linear displacements. To estimate the non-linear displacement using PSI approaches, it is common to use quite complicated models and empirical data for the region of interest [18,19,20], or assume some kind of spatial correlation of the displacement to be estimated [21]. Each received signal can be derived from the range distance Rn in any pixel at 1.the nthflowchart acquisition that is expressed by the baseline distance bn, the reference
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