In the past years, PS analysis has shown its ca- pability to treat simultaneously long series of SAR data. In this contribution an attempt is made to overcome some of the limitations of the said technique, namely its negligence of decorrelation phenomena; a maximum likelihood estimator for the physical parameters of interest is described and some results are presented. I. INTRODUCTION During the past decade the availability of long series of coherent SAR images led to the development of multiple- image processing techniques. The advantages of such joint analyses over convetional DInSAR are an increased capability in distinguishing the various contributions to the interferomet- ric phase and consequently a better estimate of atmospheric delay variations, one of the most severe limitations to accurate ground deformation recovery. We refer in particular to the PS technique (1), which has proven very effective in identifying stable scatterers, with respect to their phase properties, expecially over urbanized areas. The PS technique, in its stricter version, requires the target to possess some well defined geometrical and temporal characteristics: its cross-range extension must be limited and its reflectivity should not change over the entire data set time span. When these requirements are not met by the radar target, the estimates of physical parameters on it are considered unreliable and the point discarded. Different ways to overcome this limitation have already been proposed. With respect to temporal decorrelation we recall for instance the "Semi-PS/Temporary-PS" concept (2), tackling the case in which a target appears or disappears at some point in the amplitude time series (e.g. when a new building is contructed). Moreover, it is common practice to discard images because of their time isolation or because they represent areas temporary covered by snow (such as winter images in the Alps), since they have no or little chance to be coherent with the main bunch of the data set. With respect to geometric decorrelation we recall the SBAS technique which carries out the analysis only on small baseline subsets (3) and the so called "higher order interferometry" (4) which models the presence of two dominant scatterers in the resolution cell (with different cross-range positions). In this paper we present a new attempt of overcoming the above mentioned limitations of standard PS interferometry. The goal is to complete successful estimations of the param- eters of interest on a larger number of points. In Section II the expression of a Maximum Likelihood estimator is derived from a statistical characterization of SAR observables and real data results are presented. Eventually, some considerations are made on the underlying mechanisms of the proposed estimator and on its proximity to standard PS analysis.
['F. De Zan', 'F. Rocca']
Coherent processing of long series of SAR images