**1. Introduction**

Over almost last two decades, the differential synthetic aperture radar interferometry (DIn-SAR) technique [1, 2] has evolved to become nowadays a common practice for the detection

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and monitoring of Earth's crust modifications over time, both in academic and operative frameworks. DInSAR is mainly used to detect the temporal evolution of surface deformation through the generation of long-lasting displacement time-series. Several multi-temporal advanced DInSAR algorithms have been proposed in the literature [3–9]. At the present days, the availability of large archives of SAR images collected by several radar instruments operating with different wavelengths, and with complementary side-looking angle geometries has posed the problem to effectively combine the information associated with the different SAR datasets. In particular, the combination of multiple-platform line-of-sight (LOS) displacement time series can improve the ability to retrieve the three-dimensional (East-West, Up-Down, and North-South) components of the on-going surface displacement phenomena. Thus, it allows overcoming the main limitation of DInSAR, which is able only to measure the radar LOS projection of the displacement. This research field is of particular interest; and in the recent years, a few solutions have been proposed [10–22] based on the effective combination of multiple-orbit/multiple-angle DInSAR-based measurements, as well as on merging of DInSAR data products with external measurements (e.g., derived from processing GPS data).

In this chapter, first, the basic rationale of the multi-temporal DInSAR techniques for the generation of Earth's surface displacements maps (see Section 2) is summarized; and then, the characteristics of the principal combination techniques for multi-track/multiangle/multi-sensor SAR data recently proposed in the literature are discussed. In Section 3, the focus will be on the algorithm referred to as minimum acceleration combination technique (MinA) [23], which does not require the simultaneous process of very large sequence of differential SAR interferograms. The algorithm consists of a straightforward post-processing stage that involves the analysis of sequences of independently processed (potentially, also with different DInSAR toolboxes) multiple-platform LOS displacement time-series. Noteworthy, the adopted InSAR-combination scheme can be used in a wide context. Real SAR datasets are exploited to demonstrate the validity of the presented algorithm. Experimental results will be shown in Section 4. Conclusions and further perspectives will be provided in Section 5.
