High-precision positioning of radar scatterers

Abstract

Remote sensing radar satellites cover wide areas and provide spatially dense measurements, with millions of scatterers. Knowledge of the precise position of each radar scatterer is essential to identify the corresponding object and interpret the estimated deformation. The absolute position accuracy of synthetic aperture radar (SAR) scatterers in a 2D radar coordinate system, after compensating for atmosphere and tidal effects, is in the order of centimeters for TerraSAR-X (TSX) spotlight images. However, the absolute positioning in 3D and its quality description are not well known. Here, we exploit time-series interferometric SAR to enhance the positioning capability in three dimensions. The 3D positioning precision is parameterized by a variance-covariance matrix and visualized as an error ellipsoid centered at the estimated position. The intersection of the error ellipsoid with objects in the field is exploited to link radar scatterers to real-world objects. We demonstrate the estimation of scatterer position and its quality using 20 months of TSX stripmap acquisitions over Delft, the Netherlands. Using trihedral corner reflectors (CR) for validation, the accuracy of absolute positioning in 2D is about 7 cm. In 3D, an absolute accuracy of up to B Prabu Dheenathayalan ∼66 cm is realized, with a cigar-shaped error ellipsoid having centimeter precision in azimuth and range dimensions, and elongated in cross-range dimension with a precision in the order of meters (the ratio of the ellipsoid axis lengths is 1/3/213, respectively). The CR absolute 3D position, along with the associated error ellipsoid, is found to be accurate and agree with the ground truth position at a 99 % confidence level. For other non-CR coherent scatterers, the error ellipsoid concept is validated using 3D building models. In both cases, the error ellipsoid not only serves as a quality descriptor, but can also help to associate radar scatterers to real-world objects.

On the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR

“…Previous validation experiments using artificial targets have found that the accuracy of displacement estimates from PSInSAR analysis is at the millimetre level [15,16]. Recent advances have also seen the development of algorithms for absolute positioning of SAR scatterers using stereo SAR images of targets acquired using multiple imaging geometries [17,18]. Common to all these applications is the need for an artificial target with a geodetically known position that has been designed to have a bright and stable response in SAR imagery.…”

Applicability of satellite radar imaging to monitor the conditions of levees

“…The positioning precision is 1–2 m for C‐band data and less than 1 m for X‐band data (Dheenathayalan, Cuenca, Hoogeboom, & Hanssen, ). Using the exact PS locations, reflections from the ground can be separated from those originating from higher level objects, which may show a different deformation behaviour (Dheenathayalan, Small, Schubert, & Hanssen, ). Georeferencing is thus of high importance in the analysis of the results, in particular when the deformation is localised (Chang & Hanssen, ).…”

“…Moreover, recent approaches on estimating deformation in areas with low coherence, and in the absence of sufficient PS appear to be promising (Morishita & Hanssen, 2015a, 2015b. A low PS density can also be overcome by installing in-situ devices, that is, corner reflectors or active transponders, which provide a strong signal in the SAR images resulting in adequate deformation estimates (Dheenathayalan et al, 2016;Mahapatra et al, 2014;Sarabandi & Chiu, 1996).…”

Massive Linking of Ps-Insar Deformations to a National Airborne Laser Point Cloud

“…Millimetre per year accuracy can be achieved in deformation trend estimation. Unfortunately the source of the deformation signal is, in general, less accurately known: geolocation estimates of PS-InSAR are known with metres precision at best, depending on the sensor (Dheenathayalan et al, 2016).…”