## 1 Introduction  
Multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been widely recognized as potential remote sensing tools for monitoring ground surface movements. Such techniques overcome the drawbacks of the traditional differential radar interferometry and are capable of mapping the time-series of ground displacement within millimeter accuracy [1]. In recent years, they have been increasingly applied in tectonic movements [2, 3], land subsidence [4, 5], volcanic activities [6, 7], landslides [8, 9] and underground minims [10, 11], railways [12, 13], bridges [14, 15, 16]. One of the most classic MT-InSAR techniques is the so-called persistent scatterer interferometry (PSI), which was proposed in the early 2000s [17, 18]. This technique uses a stack of synthetic aperture radar (SAR) images, thereby isolating ground deformation signals on points with low phase dispersion by taking account into different spatial-temporal characteristics of different interferometric phase components. Such points are commonly referred to as permanent scatterers (PS). It has been repeatedly pointed out that the density of PS can be only well-preserved in urban areas. In the areas with rare human activities, it can be less than 10 PS/km\({}^{2}\)[19]. Evidently, low PS density will prevent the phenomenon of ground deformation from being comprehensively exhibited, which limits the broad practicability of the MT-InSAR techniques. Let \(N\) be the dimension of a SAR image stack, in the PSI theory, interferograms are generated with respect to a pre-selected master acquisition. That is, the phase observationsof each target will be extracted from \(N-1\) interferograms. It is unavoidable that some interferograms are with long spatial and/or temporal spans. Consequently, the corresponding interferometric signals might be severely decorrelated, leading to a decrease in stable points. To mitigate the influence of decorrelation, a series of small baseline style MT-InSAR techniques were successively proposed [20; 21; 22]. Such methods assess the decorrelation level of all possible \(N(N-1)/2\) interferometric pairs based on a pre-defined criterion (commonly using spatial/temporal baseline) and choose highly-correlated pairs for subsequent interferometric analyses. As interferometric decorrelation is induced by various of factors, it is nearly impossible to use a fixed pair selection method for all situations. In 2008, [PERSON] et al. [23] proposed a so-called phase liking method to minimize the influence of decorrelation noise. For a given point, the method firstly constructs a complex coherence matrix based on the averaged interferometric phase of every pair. Based on the coherence matrix, a maximum likelihood estimator (MLE) is defined, thereby reconstructing interferometric signals. Following the idea of phase linking, [PERSON] et al. [19] systematically proposed the SqueeSAR\({}^{\text{TM}}\) technique. The technique mainly has two distinct features. Firstly, instead of the traditional boxcar processing, a coherence matrix is constructed by averaging statistically homogeneous pixels (SHPs). The signal-to-noise ratio of a coherence matrix is hence improved. Secondly, the phase triangulation algorithm (PTA) is introduced to assure an optimum phase reconstruction result. In 2007, [PERSON] et al. [24] applied eigenvalue decomposition (EVD) to coherence matrices. The corresponding eigenvector with the largest eigenvalue can be considered to be the reconstructed interferometric signals [25]. In recent years, phase reconstruction techniques have been widely applied to various MT-InSAR applications [26; 27; 28; 29]. One of the most attractive advantage of the MT-InSAR techniques is that it is capable of providing accurate deformation time-series measurements. In order to reflect the temporal evolutions of ground displacements more comprehensive, time-series products are expected as dense as possible. Therefore, the newly launched SAR satellites usually have relatively short orbit repeat cycles.