Kanika Goel

A Distributed Scatterer Interferometry Approach for Precision Monitoring of Known Surface Deformation Phenomena

This paper presents a new technique for mapping mean deformation velocity in highly decorrelated areas with known deformation patterns, exploiting high-resolution synthetic aperture radar (SAR) data. The implemented method is based on distributed scatterers and first makes use of the Anderson-Darling (AD) statistical test to identify homogenous patches of pixels based on SAR amplitude images. Then, a robust object adaptive parameter estimation is performed to estimate the local gradients of deformation velocity and the local gradients of residual DEM in range and azimuth directions for these patches, utilizing small baseline differential interferograms. Finally, the information obtained from different patches is connected to get the deformation velocity, via a 2-D model-based deformation integration using Bayesian inference. Compared with published multitemporal interferometric work, the main advantage of the newly developed algorithm is that it does not require any phase unwrapping, and because of this, the method is largely insensitive to decorrelation phenomenon occurring in natural terrains and the availability of persistent scatterers (PSs), in contrast to the coherent stacking techniques such as PS interferometry, small baseline subset algorithm, and SqueeSAR. The method is computationally inexpensive with respect to SqueeSAR as only the small baseline interferograms are used for the processing. The method provides spatially dense deformation velocity maps at a suitable object resolution, as compared with a few measured points provided by the stacking techniques in difficult decorrelated regions. High Resolution Spotlight TerraSAR-X data set of Lueneburg in Germany is used as a processing example of this technique.

Three-Dimensional Positioning of Point Scatterers Based on Radargrammetry

This paper presents a new technique for the retrieval of 3-D point scatterer (PS) location and resolution cell configuration exploiting only the intensity of synthetic aperture radar (SAR) images. The implemented method is based on the principle of radargrammetry and makes use of Bayesian inference, wherein, directed graphs are utilized to represent dependencies of random variables and probability density functions are modeled by particle filter representations. Compared to published radargrammetric work, the newly developed algorithm optimally exploits stacks of acquisitions taken with at least three different incidence angles. Due to the large angular diversity, the method is insensitive to atmospheric propagation effects and motion of the scatterers in contrast to the coherent phase-based techniques such as persistent scatterer interferometry and SAR Tomography. Additionally, the method estimates absolute height, which is a big advantage compared to the relative estimates provided by the phase-based techniques, which moreover encounter phase unwrapping errors and temporal decorrelation. High-resolution spotlight TerraSAR-X data of Berlin central station is used as a processing example for this technique. The test case demonstrates the unambiguous absolute height estimation of PSs and resolving of complicated scattering situations (e.g., layover) in urban areas.

Measuring 3-D Surface Motion With Future SAR Systems Based on Reflector Antennae

A conventional interferometric synthetic aperture radar (SAR) system provides 1-D line-of-sight motion measurements from repeat-pass observations. Two-dimensional motions may be measured by combining two observations from ascending and descending geometries. The third motion component may be retrieved by adding a third geometry and/or by integrating along-track measurements although with much reduced precision compared to the other two components. Several options exist to improve the accuracy of retrieving the third motion component, such as combining left- and right-looking observations or exploiting recently proposed innovative SAR acquisition modes (BiDiSAR and SuperSAR). These options are, however, challenging for future SAR systems based on large reflector antennae, due to lack of capability to electronic beam steering or frequent toggle between left- and right-looking modes. Therefore, in this letter, we assess and compare the realistic acquisition scenarios for a reflector-based SAR in an attempt to optimize the achievable 3-D precision. Investigating the squinted SAR geometry as one of the feasible scenarios, we show that a squint of 13.5° will yield comparable performance to the left-looking acquisition, while further squinting outperforms this or other feasible configurations. As an optimum configuration for 3-D retrieval, the squinted acquisition is further elaborated: the different acquisition plans considering a constellation of two satellites as well as the challenges for data processing are addressed.

Thermal dilation monitoring of complex urban infrastructure using high resolution SAR data

Monitoring the deformation of urban infrastructure is crucial for improving safety and reducing economic loss. Ground deformation (caused by construction, groundwater extraction etc.) can be measured with millimeter accuracy using advanced stacking techniques in differential SAR interferometry. However, deformation might also occur due to thermal dilation of complex urban objects such as buildings and bridges, resulting in structural stress and thus, a need for monitoring. High resolution SAR missions e.g. TerraSAR-X provide a unique opportunity to measure such small seasonal displacements. This paper investigates different techniques such as Persistent Scatterer Interferometry (PSI), Distributed Scatterer Interferometry (DSI), Stable Point Network (SPN) and Small Baseline Subset Algorithm (SBAS) for thermal dilation monitoring of complex urban infrastructure using X-band SAR data.

High resolution differential interferometric stacking via adaptive spatial phase filtering

We present a new adaptive spatial filtering algorithm for accurate estimation of differential interferometric phase and coherence, to better support deformation monitoring techniques such as SBAS. The objective is high resolution interferometric phase estimation even in non-urban areas, where there is high phase noise. The typical method to enhance interferograms is a complex boxcar (rectangular) multilooking, leading to a low spatial resolution. This is a disadvantage, especially, with the launch of advanced SAR satellites such as TerraSAR-X. We propose a technique which provides improved interferograms without loosing the high geometrical resolution. Also, the coherence of the interferograms is estimated, which is important for various applications e.g. guiding phase unwrapping algorithms, selection of pixels for deformation monitoring etc. Our technique is based on identifying statistically homogenous pixels in a neighbourhood, and using them for phase flattening and finally, phase filtering via adaptive complex averaging (multilooking). We demonstrate our technique on TerraSAR-X data of Germanys Bierwang gas reservoir.

Fusion of Monostatic/Bistatic InSAR Stacks for Urban Area Analysis via Distributed Scatterers

Interferometric synthetic aperture radar (SAR) is a powerful technique providing meter-precision elevation maps and millimeter-precision surface displacement maps. Since 2007, the high-resolution SAR satellite TerraSAR-X allows monitoring of even single buildings from space using advanced monostatic repeat-pass stacking techniques. Furthermore, the launch of its twin satellite TanDEM-X in 2010 facilitates bistatic single-pass SAR interferometry. The main objective of this mission is the generation of a global digital elevation model. It also provides a configurable SAR platform for demonstrating new interferometric techniques and applications. However, in dense urban areas, standard TanDEM-X elevation models are inaccurate because ambiguities in radar layover areas cannot be solved. This letter describes the potential of joint monostatic and bistatic (motion-free and atmosphere-free) SAR interferometric stacking for an improved scene elevation and surface deformation estimation in complex urban areas. It involves exploiting distributed scatterers (DSs) using an advanced high-resolution small-baseline subset algorithm. Since most of the scatterers within a radar image can be classified as DSs, there is an increasing focus on an optimal processing of DSs for urban area monitoring. The fusion technique and an application test case are presented using a high-resolution spotlight mixed TerraSAR-X/TanDEM-X data stack of Las Vegas, USA.

Sequential estimator for distributed scatterer interferometry

The launch of the wide-swath SAR missions with short repeat-pass cycles, such as Sentinel-1, will soon provide an unprecedented large InSAR data archive. Time-series analysis on the rapidly growing data will thus become computationally demanding for a systematic monitoring of earth surface deformation. As the state-of-the-art approach in differential InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the emerging big data; an aspect to which limited attention has been dedicated. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing of the large data stacks while preserving the performance close to the Cramér-Rao Lower Bound. The performance of theof earth surface deformation. As the state-of-the-art approach in differential InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the emerging big data; an aspect to which limited attention has been dedicated. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing of the large data stacks while preserving the performance close to the Cramér-Rao Lower Bound. The performance of the proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to stacks proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to stacks of Sentinel-1 data is ongoing.

Improving the reference network in wide-area Persistent Scatterer Interferometry for non-urban areas

Advanced Interferometric SAR (InSAR) technique, namely, Persistent Scatterer Interferometry (PSI), allows long term deformation time series analysis with millimeter accuracy. Reference network arcs construction, arcs estimation and integration for PSs are an important step in PSI. In rural regions, low density of PSs leads to separate clusters during reference network construction. Also, in case of wide-area PSI using ERS-1/2 or Sentinel-1 data, the computational load can be very high. Due to this, the reference network processing is usually divided into overlapping blocks and merged later. This can however lead to spatial error propagation. This paper presents algorithms for improving the reference network in wide-area PSI, with a focus on non-urban areas.

Tandem-L performance analysis for three dimensional earth deformation monitoring

Interferometric synthetic aperture radar (InSAR) measurements are merely sensitive to the deformation along the Line of Sight (LOS) direction of the sensor. To improve the geometrical sensitivity and retrieve the three-dimensional deformation, the integration of InSAR from non-coplanar acquisitions as well as fusion with resolution-scale SAR image shift measurements has become a standard approach. Using different statistical measures, we assess and compare the influence of different image acquisition strategies as well as data fusion on the performance of InSAR in 3D deformation retrieval. Integrating nominal InSAR acquisitions, i.e. a set of measurements from ascending and descending tracks acquired from right-looking geometry, a strong correlation between the retrieved 3D parameters in the local vertical-north plane is observable. This correlation is sought to be decreased by non-nominal acquisitions; i.e. left-looking or squinted observations. These acquisition strategies are discussed for consideration in the future L-band mission Tandem-L.

Parameter estimation for distributed scatterers using high resolution SAR data

In this paper, a new approach is introduced for deformation monitoring with a focus on distributed scatterers (DSs), wherein, there is no need to unwrap the differential interferograms and the deformation is mapped at object resolution. It is based on a robust object adaptive parameter estimation using single look differential interferograms, where, the local tilts of deformation velocity and local slopes of residual DEM in range and azimuth directions are estimated. A 2D-model deformation integration is then performed using Bayesian inference to get the absolute deformation. This paper presents the technical details and a processing example of this newly developed algorithm using high resolution spotlight TerraSAR-X data of Lueneburg in Germany.