3-D Positioning and Target Association for Medium-Resolution SAR Sensors

Abstract

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.

Integration of Corner Reflectors for the Monitoring of Mountain Glacier Areas with Sentinel-1 Time Series

“…The absolute position precision was studied by computing the shift with respect to the GPS measurements, giving an RMSE of 0.83 m in 2D and 0.84 m in 3D. In comparison, an RMSE of 0.42 m in 3D was obtained with 44 ENVISAT images and two 1-m CRs, after timing correction (bistatic offset, atmospheric phase delay, solid earth tides...) and calibration offsets estimation [61]. Thus, with fewer images and without complete timing correction, the results of our study seems to be reasonable.…”

“…Since the sub-pixel precision partly depends on the SCR value [58], the SCR was estimated on each PS with the same method presented in Section 3.1.2 and the results are discussed in Section 4.2.5. Apart from atmospheric path delay, the other sources of errors in absolute positioning, such as the azimuth shift, solid earth tides or tectonics [57,[59][60][61] are not discussed in this study. Thus, a difference between PS height and LiDAR height may be due to an error in height estimation and/or due to an error in the absolute positioning.…”

Monitoring Deformation along Railway Systems Combining Multi-Temporal InSAR and LiDAR Data

“…The uncertainty in the position of the scatterers is determined by the covariance matrix, and the 3D error ellipsoid is the geometric representation of the covariance matrix. In radar coordinates, the position of a scatterer is described using the range, azimuth and cross-range coordinates [22], denoted as (r, t, c). The variance of the sub-position in azimuth and range is obtained using the estimated SCR [17]…”

“…However, often such a device is not available. Airborne LiDAR provides 3D point clouds with very high spatial density, thus LiDAR points can be found close to all radar scatterers, which makes it attractive to estimate the systematic MT-InSAR height offset based on the full CS dataset [20][21][22].…”

Absolute Localization of Corner Reflectors With Terrasar-X Spotlight Images

“…Since Eineder firstly introduced the concept of SAR imaging geodesy in 2011, many studies have demonstrated sub-meter level positioning accuracy of corner reflectors (CRs) with high resolution SAR images (Eineder et al, 2011;Cong et al, 2012;Balss et al, 2012;Balz et al, 2016). After carefully correcting the noise caused by atmospheric delays and Earth motion, the absolute geolocation in ITRF reference frame at centimeter-level can be obtained in case of TerraSAR-X (Schubert et al, 2010;Gisinger et al, 2015) and decimeter-level in case of Sentinel-1A/B (Schubert et al, 2017;Dheenathayalan et al, 2018). In this paper, we present our experiment of 3D absolute localization results with high-resolution Spotlight-mode TerraSAR-X images.…”