ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2020
https://doi.org/10.5194/isprs-annals-V-3-2020-141-2020
https://doi.org/10.5194/isprs-annals-V-3-2020-141-2020
03 Aug 2020
 | 03 Aug 2020

SELECTION OF PERSISTENT SCATTERER INTERFEROMETRIC SYNTHETIC APERTURE RADAR MASTER IMAGE CONSIDERING TEMPORAL BASELINE, SPATIAL BASELINE AND DOPPLER CENTROID FREQUENCY DIFFERENCE

Y. Lu, J. Zhang, X. Tong, X. Lu, W. Han, H. Zhang, H. Zhao, and X. Liu

Keywords: PS-InSAR, Master Image, Minimum Three Baselines, Optimization Selection

Abstract. This paper proposed a new algorithm master Image Temporal Spatial baseline, Doppler centroid frequency difference (MITSD) to select the PS-InSAR common master image (CMI), by using the sum of temporal baselines, spatial baselines, and Doppler centroid frequency differences as a reference. The existing persistent scatterer interferometric synthetic aperture radar (PS-InSAR) common master images election method is affected by three baseline factors: temporal baseline, spatial baseline, and Doppler centroid frequency differences, then one single baseline factor in the three baselines being too large or above the baseline threshold will cause the decoherence. This method normalizes the temporal baseline, spatial baseline, and Doppler centroid frequency baseline to the same order of magnitude, and then the results of baseline optimization are summed up as the minimum coherence. Simultaneously,the algorithm in this paper sets each limit the average value of each baseline as a threshold to reduce the influence of a single baseline. The C-band Sentinel-1A single-look complex (SLC) image data (VV-polarization) in the study area was used as experimental data to compare with the MITSD, the current MSTB (minimum sum of three baselines), and CCCM (comprehensive correlation coefficient method). The results showed that (a) the baseline optimization method was more reasonable and reliable in the selection of the master image in PS-InSAR technology; and (b) in this method, the calculation steps were reduced into the calculation process, and the model was more concise than other algorithms.