Coherency Matrix Decomposition-Based Polarimetric Persistent Scatterer Interferometry

Abstract

The rationale of polarimetric optimization techniques is to enhance the phase quality of the interferograms by combining adequately the different polarization channels available to produce an improved one. Different approaches have been proposed for Polarimetric Persistent Scatterer Interferometry (PolPSI). They range from the simple and computationally efficient BEST, where for each pixel the polarimetric channel with the best response in terms of phase quality is selected, to those with high computational burden like the Equal Scattering Mechanism (ESM) and the Sub-Optimum Scattering Mechanism (SOM). BEST is fast and simple but it does not fully exploit the potentials of polarimetry. On the other side, ESM explores all the space of solutions and finds the optimal one but with a very high computational burden. A new PolPSI algorithm, named CMD-PolPSI, is proposed to achieve a compromise between phase optimization and computational cost. Its core idea is utilizing the PolSAR coherency matrix decomposition to determine the optimal polarization channel for each pixel. Three different PolSAR image sets of both full-(Barcelona) and dual-polarization (Murcia and Mexico City) have been used to evaluate the performance of CMD-PolPSI. The results show that CMD-PolPSI presents better optimization results than BEST method by using either DA or temporal mean coherence as phase quality metrics. Compared with the ESM algorithm, CMD-PolPSI is 255 times faster but its performance is not as optimal. The influence of the number of available polarization channels and pixel's resolutions on the CMD-PolPSI performance is also discussed.

Polarimetric Persistent Scatterer Interferometry for Ground Deformation Monitoring with VV-VH Sentinel-1 Data

“…As more and more sattelites with the capability of acquiring PolSAR images (e.g., Radarsat-2, ALOS-2, TerraSAR-X, and Sentinel-1) have been launched, it is possible to extend the PolPSI techniques from the Ground-based SAR images to satellite SAR images. Under this circumstance, more PolPSI algorithms have been proposed [28][29][30][31][32][33][34][35][36][37][38][39].…”

“…A phase quality metric has to be chosen for pixels polarimetric optimization in PolPSI. Generally, like the conventional PSI methods, the amplitude dispersion index (ADI, better for PS pixels' optimization) [26,33,36] and coherence (better for DS pixel optimization) [25,28,29,36] are the two commonly used phase quality metrics. Similarly with DS-InSAR, more advanced PolPSI techniques are proposed to adaptive optimize PS and DS pixels by using the combination of ADI and coherence [31,34,37,38].…”

“…Similarly with DS-InSAR, more advanced PolPSI techniques are proposed to adaptive optimize PS and DS pixels by using the combination of ADI and coherence [31,34,37,38]. Therefore, according to the phase quality metrics used, the most commonly used PolPSI techniques can be classified into three main categories, i.e., PolPSI-ADI (PolPSI with the amplitude dispersion index as the phase quality metric) [26,33,36], PolPSI-COH (PolPSI with the coherence as the phase quality metric) [25,28,29,36], and PolPSI-AOS (PolPSI with the adaptive optimization strategies) [31,34,37,38]. Different PolPSI algorithms are with different phase optimization performances, and suitable for different scenarios [36,37].…”

“…Therefore, according to the phase quality metrics used, the most commonly used PolPSI techniques can be classified into three main categories, i.e., PolPSI-ADI (PolPSI with the amplitude dispersion index as the phase quality metric) [26,33,36], PolPSI-COH (PolPSI with the coherence as the phase quality metric) [25,28,29,36], and PolPSI-AOS (PolPSI with the adaptive optimization strategies) [31,34,37,38]. Different PolPSI algorithms are with different phase optimization performances, and suitable for different scenarios [36,37]. Although it is possible to apply PolPSI techniques on satellite SAR images for ground deformation monitoring over broader areas, the free available time-series PolSAR images are far away from enough for PolPSI applications.…”

“…In 2018, Roghayeh Shamshiri incorporates VH channel Sentinel-1 images with commonly used VV one for Trondheim city ground deformation monitoring using the PolPSI-ADI method, demonstrating the advantages of employing sentinel-1 dual-pol SAR images for PSI applications [41]. Almost at the same time, an advanced PolPSI-COH technique [34] and the coherency matrix decomposition (CMD) method (which can be used as both PolPSI-ADI and POlPSI-COH) [36] have been proposed and evaluated on Sentinel-1 PolSAR images over San Fernando Valley and Mexico city, respectively. These studies have demonstrated the effectiveness of PolPSI with Sentinel-1 PolSAR images, and researchers have shown an increased interest in PolPSI techniques recently [39,42,43].…”