Persistent Scatterer Interferometry (PSI) is a time series remote sensing technique to estimate displacements of geo-objects from the interferometric phases of selected Persistent Scatterers (PS). The relative position of a scatterer within a resolution cell causes an additional phase contribution in the observed phase, which needs to be accounted for in PSI processing. Here we analyze the influence of this sub-pixel position correction on point localization and displacement quality. Apart from a theoretical evaluation, we perform experiments with TerraSAR-X, Radarsat-2, and Sentinel-1, demonstrating various levels of improvement. We show that the influence of the sub-pixel correction is significant for the geolocation of the scatterer (meter-level improvement), modest for the elevation estimation (centimeter-level improvement), and limited for the displacement estimation (submillimeter-level). For displacement velocities, we find variations of a few tenths of a millimeter per year. The effect of sub-pixel correction is most dominant for large orbital baselines and short time series.

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Persistent scatterers (PSs) are coherent measurement points obtained from time series of satellite radar images, which are used to detect and estimate millimeter-scale displacements of the terrain or man-made structures. However, associating these measurement points with specific physical objects is not straightforward, which hampers the exploitation of the full potential of the data. We have investigated the potential for predicting the occurrence and location of PSs using generic 3-D city models and ray-tracing methods, and proposed a methodology to match PSs to the pointlike scatterers predicted using RaySAR, a ray-tracing synthetic aperture radar simulator. We also investigate the impact of the level of detail (LOD) of the city models. For our test area in Rotterdam, we find that 10% and 37% of the PSs detected in a stack of TerraSAR-X data can be matched with point scatterers identified by ray tracing using LOD1 and LOD2 models, respectively. In the LOD1 case, most matched scatterers are at street level while LOD2 allows the identification of many scatterers on the buildings. Over half of the identified scatterers easily correspond to identify double or triple-bounce scatterers. However, a significant fraction corresponds to higher bounce levels, with approximately 25% being fivefold-bounce scatterers.@en

Time-series synthetic aperture radar interferometry (InSAR) has evolved into a widely preferred geodetic technique for measuring topography and surface deformation of the earth. In the last decades, time-series InSAR methodologies were developed to extract information from persistent scatterers (PS) and distributed scatterers (DS). Methodologies based on DSs extract information from pixels from the natural terrain. Persistent Scatterer Interferometry (PSI) extracts information from PSs, which are found in abundance in areas with man-made infrastructure. However, a satisfactory geodetic application of these methodologies requires a complete understanding of the measurement principles, an identification of radar scatterers in the physical world, and an interpretation of the estimated deformation. Moreover, for areas not suitable for coherent imaging adding new measurements is not trivial. In consideration of the above challenges, the two main objectives of this study are: (i) to develop a systematic method to decode PSI measurements, i.e., identify PSs in the object space in order to interpret the estimated deformation (kinematics), and (ii) to assess the feasibility of encoding artificial radar scatterers, i.e. adding new measurements using radar reflectors, at places where there exists no coherent InSAR measurements. We review the contents of SAR resolution cell and the time-series processing methodologies with special focus on the Delft implementation of PSI processing. A physical interpretation of the time-series InSAR results is shown possible by decoding what the radar has measured and understanding the deformation phenomena. We employ two approaches to perform this decoding. First is to identify the source of the radar reflection by characterizing and associating PSs to a target type. By using only InSAR data, we apply an iterative classification method to discriminate radar scatterers between the ground level and elevated infrastructure. We combine the limited classification output with deformation rate and identify various deformation phenomena such as shallow compaction, no relative motion, autonomous structural motion, local land subsidence, and inter-structural deformation. In particular, we introduce a parameter known as RDI (Relative Deformation Index) to detect, quantify and analyze the regions subject to relative deformation for infrastructural stability analysis. The feasibility of this approach is successfully demonstrated with underground gas-pipe and water-pipe network monitoring applications over Amsterdam and The Hague, respectively. Second, a point-level (object or sub-object level) linking of radar reflections to real-world objects. For this step, a precise 3D position of the scatterers is derived. Applying corrections for various position error sources, accurate 3D position of scatterers is achieved for high-resolution and medium-resolution SAR imagery. A standard Gauss-Markov approach is applied to facilitate error propagation and quality assessment and control. The 2D and 3D position capabilities are validated using trihedral corner reflector field experiments. In order to precisely associate radar scatterers to physical objects, we introduce an approach to use a 3D building model of the physical objects. Linking of scatterers to parts of infrastructure is demonstrated for high-resolution and medium-resolution imagery. Finally, we propose the concept of small radar reflectors to introduce new coherent reflections. The small reflectors are designed such that they are visible from both ascending and descending imaging directions, enabling vector decomposition of deformation measurements. These small radar reflectors act as weak point scatterers. To achieve a desired SCR (Signal to Clutter Ratio), many small reflectors are distributed over an area and averaged. The detection of small reflectors is achieved by distributing them in a predefined spatial pattern. In this study, a new interferometric phase expression is derived to estimate a phase standard deviation for low-SCR and high-SCR targets. The proposed concept is experimentally validated using X-band satellite data over a grassy terrain in the Netherlands. The results indicate that distributed corner reflectors can provide deformation measurements with millimeter precision. @en

To correctly interpret the estimated displacements in InSAR point clouds, especially in the built environment, these need to be linked to real-world structures. This requires the accurate and precise 3D positioning of each point. Artificial ground control points (GCPs), such as corner reflectors, serve this purpose, but since they require efforts and resources, there is a need for criteria to assess their usefulness. Here we evaluate the value and necessity of using GCPs for different scenarios, concerning the required efforts, and compare this to alternatives such as digital surface models (DSM) and advanced (geo) physical corrections. We consider single-epoch as well as multi-epoch GCP deployment, reflect on the number of GCPs required in relation to the number of SAR data acquisitions, and compare this with digital surface models of different quality levels. Analyzing the geolocation performance using TerraSAR-X and Sentinel-1 data, we evaluate the pros and cons of various deployment options and show that the multi-epoch deployment of a GCP yields optimal geolocalization results in terms of precision, accuracy, and reliability.@en

Associating a radar scatterer to a physical object is crucial for the correct interpretation of interferometric synthetic aperture radar measurements. Yet, especially for medium-resolution imagery, this is notoriously difficult and dependent on the accurate 3-D positioning of the scatterers. Here, we investigate the 3-D positioning capabilities of ENVISAT medium-resolution data. We find that the data are perturbed by range-and-epoch-dependent timing errors and calibration offsets. Calibration offsets are estimated to be about 1.58 m in azimuth and 2.84 m in range and should be added to ASAR products to improve geometric calibration. The timing errors involve a bistatic offset, atmospheric path delay, solid earth tides, and local oscillator drift. This way, we achieve an unbiased positioning capability in 2-D, while in 3-D, a scatterer was located at a distance of 28 cm from the true location. 3-D precision is now expressed as an error ellipsoid in local coordinates. Using the Bhattacharyya metric, we associate radar scatterers to real-world objects. Interpreting deformation of individual infrastructure is shown to be feasible for this type of medium-resolution data.@en

The geolocation of coherent radar scatterers, used for InSAR deformation analysis, is often not accurate enough to associate them to physical geo-objects. The imaging geometry of satellite InSAR results in (i) biases in the entire point field, and (ii) quite elongated and skewed confidence ellipsoids in the range, azimuth and cross-range direction. The metric defined by the covariance matrix of the InSAR results defines the optimal way to associate scatterers with geo-objects. Laser scanning point clouds, stemming from aerial or terrestrial laser surveys, yield very dense geometry of geo-objects and topography. Here we combine InSAR and laser point clouds, taking the covariance metrics of the InSAR data into account. This enables us to correct the positions of InSAR data, to provide a geometric match with geo-objects. We demonstrate how this allows for adding contextual information as attributes to individual scatterers, which improves the interpretation of the InSAR results. @en

In recent years, synthetic aperture radar interferometry has become a recognized geodetic tool for observing ground motion. For monitoring areas with low density of coherent targets, artificial corner reflectors (CRs) are usually introduced. The required size of a reflector depends on radar wavelength and resolution and on the required deformation accuracy. CRs have been traditionally used to provide a high signal-to-clutter ratio (SCR). However, large dimensions can make the reflector bulky, difficult to install and maintain. Furthermore, if a large number of reflectors are needed for long infrastructure, such as vegetation-covered dikes, the total price of the reflectors can become unaffordable. On the other hand, small reflectors have the advantage of easy installation and low cost. In this paper, we design and study the use of small reflectors with low SCR for ground motion monitoring. In addition, we propose a new closed-form expression to estimate the interferometric phase precision of resolution cells containing a (strong or weak) point target and a clutter. Through experiments, we demonstrate that the small reflectors can also deliver displacement estimates with an accuracy of a few millimeters. To achieve this, we apply a filtering method for reducing clutter noise.

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In persistent scatterer (PS) interferometry, the relatively poor 3D geolocalization precision of the measurement points (the scatterers) is still a major concern. It makes it difficult to attribute the deformation measurements unambiguously to (elements of) physical objects. Ground control points (GCP's), such as corner reflectors or transponders, can be used to improve geolocalization, but only in the range-azimuth domain. Here, we present a method which uses only one GCP, visible in only one single radar acquisition, in combination with a digital surface model (DSM) data to improve the geolocation precision, and to achieve an object snap by projecting the scatterer position to the intersection with the DSM model, in the metric defined by the covariance matrix (i.e. error ellipsoid) of every scatterer.@en

The main challenge in analyzing the results of persistent scatterer techniques is to associate each coherent radar reflection to a real-world object, referred to as target type classification. In recent years different methods to perform target type classification were studied. In this paper we propose a height-based target type classification method to discriminate radar reflections emanating from the ground and above-ground objects. Data acquired from multiple spaceborne satellites such as ERS, Envisat, and TerraSAR-X covering Amsterdam, the Netherlands spanning over two decades from 1992 to 2012 are processed. The target classification results are validated with highly precise elevation data obtained from an independent airborne laser altimetry technique. In this paper we demonstrate that our target type classification method is accurate and thereby the generated DEM of the ground is of nearly sub-metric accuracy in case of ERS and Envisat, and TerraSAR-X.@en

Detecting a point-like target when it is horizontally displaced is of paramount importance in target tracking and in measuring the motion of glaciers over short intervals of time. This paper performs an experimental study of the accuracy, precision and sensitivity of the horizontal motion detectable using SAR. Therefore point-like targets such as corner reflectors (CR) are moved horizontally in a controlled manner over short time intervals to reproduce the real target motion. Such CR movements are monitored using SAR and the results are compared with the ground truth to arrive at the target horizontal motion determination parameters. Towards this goal three CRs were installed each displaced by a few hundreds of metres in a farmland in Delft, The Netherlands. These corner reflectors are inclined for ERS-2 3-days ice-phase mission starting March 2011. Since the area does not exhibit horizontal motion, one of the CRs was moved horizontally stepwise in the order of a few centimeters to a few metres. At each step the CRs are imaged by SAR and also measured by campaign-style GPS (and with a few leveling campaigns) in order to provide the actual displacement in three dimensions. Then the motion is computed using SAR data and results are compared with the GPS measurements to validate the sensitivity of SAR in detection of motion of the targets. The experimental setup is such that the CRs are visible starting from March 2011 from both ascending and descending orbit TerraSAR-X satellite acquisitions over Delft. Hence similar parameters such as sensitivity, precision and accuracy of motion detection will be derived for X-band SAR as well. Further, in order to substantially verify the reliability of our computations, data from three different field experiments with stable CRs performed with ERS-1/2 in 1996, with ENVISAT from 2003 to 2007 and with ENVISAT from March 2010 to January 2011 in the areas of Groningen, Delft and Cabauw respectively were exploited. The outcome of our experiment will result in the empirical study of the sensitivity of motion detection of point-like targets in C- and X- bands. Also the influence of these parameters under varying imaging conditions such as change in Doppler and perpendicular baselines will be discussed. @en

Persistent Scatterer Interferometry (PSI) has emerged over the last decade as a technique capable of very accurate (millimetric) measurements of ground deformation occurring at radar scatterers (persistent scatterers or PS) that are phase coherent over a period of time. PSI studies using C-band SAR data have shown that the PS spatial density in urban areas is usually very high (100-300 PS/km2). However, many ground deformation phenomena (e.g. tectonic motion, volcanoes, landslides, mining, gas extraction, CO2 sequestration) occur in uninhabited or rural areas with few man-made structures, leading to much lower PS density because of significant phase decorrelation between subsequent SAR acquisitions. In order for PSI to be effective in monitoring these areas, it has been found that a PS density greater than about 10 PS/km2 is required. Artificial amplitude- and phase-stable radar scatterers may thus have to be introduced in non-urbanised geodynamic areas that have too low a density of PS points. Conceptually the simplest of these artificial PS points are corner reflectors. Several experiments have been performed in the past using these reflectors, with conclusive results about their amplitude and phase stability. They suffer, however, from the disadvantage of large size (in the order of a metre in case of C-band SAR). To make these artificial PS points easy to deploy and maintain, especially in poorly accessible areas, Compact Active Transponders (CATs) have been designed to be used in lieu of corner reflectors. These CATs are small (in the order of a few tens of centimetres), lightweight (<3 kg), less obtrusive, and have the added advantage of a better link budget due to signal amplification by the transponder. They are sealed, function autonomously with internal power and over a wide temperature range, and can operate unattended for more than a year. Additionally, since a CAT is transmitter-specific and is only turned on at the time of the satellite overpass, it offers little interference to other radar or radio targets. However, it is of paramount importance in geodetic applications to ensure that the phase of the CAT remains stable in all operating and environmental conditions. Towards this goal, an experiment to validate the phase stability of CATs has been set up in a farmland in Delft (The Netherlands). The setup comprises three CATs and three corner reflectors, which are installed at distances of a couple of hundred metres from each other. SAR data from the ERS-2 Ice-Phase Mission are being acquired every three days between March and June 2011. Since the area does not exhibit steady ground deformation, some of the units are displaced vertically by a controlled amount. Levelling is performed between the CATs and the corner reflectors as close as possible to each SAR acquisition, in order to validate the height differences obtained from the radar phase information. As a second means of validation, campaign-style GPS is performed on each of the devices to accurately position them in WGS-84 coordinates. One of the CATs in the Delft field experiment has an integrated GPS antenna, to ensure millimetric coregistration and a coherent cross-reference. This novel unit called I2GPS (Integrated Interferometry and GNSS for Precision Survey) has been developed with the objective of producing a fully-integrated deformation map. In addition to providing absolute calibration for PSI data, the high temporal sampling rate of GPS data imparts the capability of accurately detecting abrupt ground motion in three dimensions. With adequate GPS/I2GPS units, the vertical components of the local velocity field can be derived from single-track InSAR line-of-sight displacements. The results and conclusions of this experiment consisting of corner reflectors, CATs and I2GPS will be presented and analysed here.@en