Sub-band InSAR Technology Based On High-Resolution SAR Data And Its Application To Mapping Of Coseismic Deformation

The traditional interferometric synthetic aperture radar (InSAR) technology has been successfully applied into terrain mapping and deformation monitoring in recent decades years. Its accuracy and reliability depends on error calibration and phase unwrapping correctly in data processing. The goal of phase unwrapping is to calculate the absolute phase from wrapping phase which is moduled by 2 π. A variety of unwrapping algorithms proposed by many scholars have greatly promoted the development of InSAR technology. However, most of them show its own limitations in complicated surface environments. Different unwrapping algorithms gave different results for the same interferogram in some cases because of low coherence. Especially for complex terrain and deformation areas, steep topography and large-slope deformation will result in dense interferometric fringes in a small area on the interferogram, which would cause difficulty for the subsequent phase filtering, thus leading to erroneous phase unwrapping.Sub-band InSAR technique makes it attractive by avoiding unwrapping the phase or reducing the number of interfermetric fringes to a few, which is realized by using a effective longer wavelength from shortening chirp bandwidth of the signal. The difficulty of phase unwrapping is dramatically decreased or skipped compared with the InSAR. Whereas, shortening the bandwidth of the signal decrease the ratio of signal to noise of interferogram because of the disturbation from sidelobes. The accuracy is heavily depends on the central frequency and the selection of bandwidth. Therefore, parameters optimalization, noise filtering and special processing strategy in data processing is needed to assure the precision and reliability of the sub-band InSAR. The basic principle and steps of data processing of sub-band InSAR are presented firstly in this thesis, the optimal parameters for the center frequency and bandwidth of sub-band are selected by a series of experiments conducted to extract DEM from TerraSAR-X data which covered the Ayers Rock in Australia by using sub-band InSAR. Based on the optimal parameters, the coseismic deformation of the 2013 Mw7.7 Pakistan Earthquake is extracted using sub-band InSAR. The cross-validation is carried out by comparing the sub-band InSAR results with the ones from offset-tracking, D-InSAR, cross-spectrum correlation method based on Landsat 8 optical images, and simulation finally. The primary achievements are summarized as below:1. Based on the analysis on the resolution, chirp bandwidth and working waveband of SAR, we conclude that the new generation SAR system with wide chirp bandwidth is suitable for sub-band InSAR application now. The classification and advance of phase unwrapping is presented, and strength and weakness of various unwrapping algorithms is summarized. The difficulties in sub-band InSAR are put forward theoretically and practically based on analyzing present-day researches on sub-band InSAR.2. The band-pass filter for complex signal and calibration technique for trend error in interferograms involved in sub-band InSAR is well studied. Based on the relationship between chirp bandwidth and range resolution of SAR, a band-pass filter based on SLC image sub-band division is put forward to implement filtering complex signal. For the linear trend errors in sub-band InSAR, a method combining narrow band trap filter with Chirp-Z restrain is proposed to remove it3. The strategy for selecting optimal parameters of center frequency and bandwidth in sub-band InSAR is designed. A series of experiments are conducted to extract DEM from real data using sub-band InSAR. The optimal parameter scheme is determined by comparing the experimental results and SRTM DEM. Meanwhile, we found that reducing inter-spectrum disturbation and improving resolution contradict each other.4. For the first time, we extracted successfully coseismic deformation field of 2013 Mw7.7 Pakistan Earthquake by using sub-band InSAR based on the optimal parameters selected above. Its agreement with D-InSAR result confirmed the practicability of the sub-band InSAR. Comparison between the result from sub-band InSAR and those from offset-tracking based on SAR image and Landsat 8 optical image, simulation etc., shows that sub-band InSAR gave us a better result with higher precision, which presents more details of deformation field.5. By analyzing characteristics of sub-band InSAR phase distribution, we found that sub-band InSAR less depends on the coherence of interferogram than conventional InSAR, instead more depends on the existence of interfermetric fringes. A method is developed to detect fringe frequency based on conventional InSAR interferograms.