## 1 Introduction  
As is well known, the study of ground deformation experienced a major breakthrough in 1990s with the development of space-based observation techniques. An important element in this has been the advent of synthetic aperture radar interferometry (InSAR) that can reveal details of the deformation in complex areas [1; 2; 3; 4; 5; 6]. In order to overcome the limitations of the conventional InSAR technique, i.e., spatial-temporal decorrelation and atmospheric artifacts, the persistent scatterer InSAR (PSInSAR) technique was developed in late 1990s [7; 8]. The technique takes the phase difference between adjacent pixels that have strong backscattereing features during the whole time span as observations in order to suppress the spatial-temporal decorrelation and atmospheric artifacts. Many algorithms have subsequently been proposed to enhance the robustness and applicability of PSInSAR [9; 10; 11]. Over the years the application of PSInSAR has been widely performed, ranging from monitoring ground deformation in urban and nonurban areas (e.g., [12; 13; 14; 15; 16; 17; 18]) to monitoring single infrastructures, such as dams and buildings (e.g., [19; 20; 21; 22]). However, the PSInSAR technique generally needs more than 30 scenes of SAR images to guarantee the validity of the selected coherent points [8]. Additionally, the accuracy of PSInSAR-derived displacement benefits from a reliable searching in the predefined solution space, which depends on the high density of coherent points. This is, however, not always satisfied in the investigation of linear infrastructures, such as bridges, motorways, and pipelines, especially with moderate-resolution SAR data [23; 24; 25; 26; 27; 28; 29]. Temporal coherent point InSAR (TCPInSAR) is a well-developed multi-temporal technique that can identify and co-register the coherent points with a small number of SAR acquisitions and estimate the surface displacement without the requirement of either 3D phase unwrapping or solution space searching [30; 31]. The approach has been successfully applied in the monitoring of urban ground deformation, mining-induced subsidence, interseismic deformation, and landslides, with a large or moderate set of observations [32; 33; 34; 35]. In this paper, we experiment to extend the application of the TCPInSAR technique to monitor the deformation of linear infrastructure with emphasis on using a small dataset of SAR images. The studied linear infrastructure is the Donghai Bridge, which is located in the north of Hangzhou Bay in the East China Sea and has a length of 32.5 km over the sea and 3.7 km over the land, respectively (Figure 1). The width of the bridge is 31.5 m, including twin decks and a six-lane dual carriageway. Donghai Bridge was built by using the concrete placing method, with construction starting on 26 June 2002, with completion after 35 months. There is a two-way main navigation hole in the bridge, which has the navigable clear height of 40 m and allows the navigation of 5000 t ships. This section of the bridge is suspended by 192 cables, which are supported by two towers with heights of 159 m. As the fourth longest cross-sea bridge in the world, the Donghai Bridge links mainland Shanghai with Yangshan Deep-Water Port. Reliably monitoring the deformation of such a long-span bridge is of great importance to assess its structural safety [24]. Compared with continuous GPS data, which have been widely used to monitor long bridges, InSAR measurements can provide much denser spatial samples along the bridge with no need of installing ground instruments. However, as a crucial step in InSAR processing, accurate co-registration between SAR images is challenging over areas largely occupied by the featureless sea surface. In the conventional method, where evenly-distributed windows are used to obtain the offsets between the master and slave images, the offsets over the sea area can distort the co-registration polynomial fitting, even though there is a predefined threshold to remove the inaccurately-estimated offsets.