Real-time Processing of Ground Based Synthetic Aperture Radar (GB-SAR) Measurements

In the last years, Ground based Synthetic Aperture Radar (GB-SAR) has proven to be a powerful tool for monitoring displacements and deformation that accompany mass movements like e.g. landslides, glaciers and volcanic hazards. The goal of this thesis is to develop a real-time capable technique that allows to analyse GB-SAR data and assess the state of a mass movement with the least delay possible after a GB-SAR measurement is acquired. The GB-SAR instrument IBIS-L allows the remote monitoring of an object at a distance of up to 4 km by transmitting microwaves at a frequency of 17.2 GHz and receiving the reflected echoes. Every 5 to 10 minutes, it delivers a twodimensional amplitude and phase image with a range resolution of 0.75 m and a cross-range (azimuth) resolution of 4.4 mrad (4.4 m at a distance of 1 km). The amplitude depends on object geometry and reflectivity. By computing the difference of two phase images observed at two different points in time, displacements in line-of-sight can be derived for each resolution cell. Only relative phase differences can be formed (ranging between -pi and +pi), thus, the number of full phase cycles (i.e. phase ambiguity) is unknown. Apart from displacements, the phase difference is also influenced by atmospheric disturbances and noise. To determine displacements, it is necessary to unwrap the phase differences (i.e. determine the phase ambiguities) and estimate the atmospheric effect for each resolution cell and for each time step. Many different methods exist for phase unwrapping, mainly developed for spaceborne SAR. The term Persistent Scatterer Interferometry (PSI) describes a set of techniques, which analyses only phase time series at persistent scatterers (PS), i.e. resolution cells with a good phase standard deviation (usually less then 0.3 to 0.4 rad) (Ferretti et al., 2001; Kampes, 2006). The common PSI methods are, however, not directly real-time capable as they analyse time series. The real-time analysis tool described in this thesis is especially designed for GB-SAR requirements. It is a combination of PSI with Multi Model Adaptive Estimation (MMAE) (Marinkovic et al., 2005; Brown and Hwang, 1997). The PS are selected according to Ferretti et al. (2001) using the amplitude dispersion index, which describes the phase accuracy. Only a subset of this selection, the PS candidates (PSC), are used for phase unwrapping and estimation of the atmosphere. Due to temporal changes of PS quality, caused by e.g. rock falls, the PSC selection is changing with time. To simplify the unwrapping, the ambiguities are not estimated from the time series itself but rather on the difference of the time series of two neighbouring PSC. By that the atmospheric effect is reduced. For each possible ambiguity solution of a time series difference, a Kalman Filter exists to sequentially estimate the state of a kinematic process. At each time step new observations are added to the filter. The best ambiguity solution is selected based on probabilities, which are computed from the difference between observed and predicted phase. After this temporal unwrapping, a spatial unwrapping is performed for each time step to make sure that the determined solution is spatially consistent. The atmospheric effect is estimated after the unwrapping using a combination of meteorological data and filtering. Finally, the remaining PS are integrated into the network. With this technique, a first estimation of the displacements at the PS is available a few seconds to minutes after the data acquisition. With every time step, new observations are added, which will improve the determination of ambiguities until they can be fixed. Thus, the final estimation of displacements is available a few minutes to one hour after the data acquisition. The performance of the technique is shown by unwrapping synthetic data and real data from observation campaigns at four different locations: a quarry in Dieburg, Germany, a mountain side in Bad Reichenhall, Germany, a caldera flank on Sao Miguel, Azores and a landslide near Innsbruck in the Austrian Alps.