Heike Peter

Bio: Heike Peter is an academic researcher. The author has contributed to research in topics: Orbit determination & Satellite. The author has an hindex of 3, co-authored 8 publications receiving 66 citations.

Sentinel-3A: Validation of Orbit Products at the Copernicus POD Service

Abstract: The Copernicus POD (Precise Orbit Determination) Service is part of the Copernicus PDGS Ground Segment of the Sentinel-1, -2, and -3 missions. It is responsible of generating precise orbital products and auxiliary data files for their use as part of the respective PDGS processing chains.

Copernicus Sentinel-1 satellites: sensitivity of antenna offset estimation to orbit and observation modelling

Abstract: . The SAR (Synthetic Aperture Radar) Copernicus Sentinel-1 satellites require a high orbit accuracy of 5 cm in 3D in comparison to external processing facilities. The official orbit products delivered by the Copernicus POD (Precise Orbit Determination) Service fulfil this requirement. Nevertheless, analyses have shown discrepancies in the orbit results for the two satellites Sentinel-1A and Sentinel-1B. Since the satellites are identical in construction estimated orbit parameters like the scale factor for the radiation pressure are expected to be at the same magnitude, which is not the case. Estimation of GPS antenna offsets leads to differences between the two satellites, which might explain the discrepancies in the estimated orbit parameters. Such offset estimations are, however, very sensitive to orbit and observation modelling. It has to be assured that the results are not biased by insufficient models. First of all, stabilisation of the antenna offset estimation is achieved by improving the observation modelling by applying single receiver ambiguity resolution. The Copernicus Sentinel-1 satellites have a very complex shape with the long SAR antenna and the two large solar arrays. Antenna offset estimation based on different satellite models may give results which differ by up to 1.5 cm. The dispersion of the estimates is quite large depending also on eclipse and non-eclipse periods. Consideration of simple assumptions on satellite self-shadowing effects improves the satellite model and also the results of the antenna offset estimation. Finally, more consistent results for the two Sentinel-1 satellites are achieved by applying the antenna offset estimates.

Precise orbit determination of the Sentinel-3A altimetry satellite using ambiguity-fixed GPS carrier phase observations

Abstract: The Sentinel-3 mission takes routine measurements of sea surface heights and depends crucially on accurate and precise knowledge of the spacecraft. Orbit determination with a targeted uncertainty of less than 2 cm in radial direction is supported through an onboard Global Positioning System (GPS) receiver, a Doppler Orbitography and Radiopositioning Integrated by Satellite instrument, and a complementary laser retroreflector for satellite laser ranging. Within this study, the potential of ambiguity fixing for GPS-only precise orbit determination (POD) of the Sentinel-3 spacecraft is assessed. A refined strategy for carrier phase generation out of low-level measurements is employed to cope with half-cycle ambiguities in the tracking of the Sentinel-3 GPS receiver that have so far inhibited ambiguity-fixed POD solutions. Rather than explicitly fixing double-difference phase ambiguities with respect to a network of terrestrial reference stations, a single-receiver ambiguity resolution concept is employed that builds on dedicated GPS orbit, clock, and wide-lane bias products provided by the CNES/CLS (Centre National d’Etudes Spatiales/Collecte Localisation Satellites) analysis center of the International GNSS Service. Compared to float ambiguity solutions, a notably improved precision can be inferred from laser ranging residuals. These decrease from roughly 9 mm down to 5 mm standard deviation for high-grade stations on average over low and high elevations. Furthermore, the ambiguity-fixed orbits offer a substantially improved cross-track accuracy and help to identify lateral offsets in the GPS antenna or center-of-mass (CoM) location. With respect to altimetry, the improved orbit precision also benefits the global consistency of sea surface measurements. However, modeling of the absolute height continues to rely on proper dynamical models for the spacecraft motion as well as ground calibrations for the relative position of the altimeter reference point and the CoM.

Soil Salinity Mapping Using SAR Sentinel-1 Data and Advanced Machine Learning Algorithms: A Case Study at Ben Tre Province of the Mekong River Delta (Vietnam)

Abstract: Soil salinity caused by climate change associated with rising sea level is considered as one of the most severe natural hazards that has a negative effect on agricultural activities in the coastal areas in most tropical climates. This issue has become more severe and increasingly occurred in the Mekong River Delta of Vietnam. The main objective of this work is to map soil salinity intrusion in Ben Tre province located on the Mekong River Delta of Vietnam using the Sentinel-1 Synthetic Aperture Radar (SAR) C-band data combined with five state-of-the-art machine learning models, Multilayer Perceptron Neural Networks (MLP-NN), Radial Basis Function Neural Networks (RBF-NN), Gaussian Processes (GP), Support Vector Regression (SVR), and Random Forests (RF). For this purpose, 63 soil samples were collected during the field survey conducted from 4–6 April 2018 corresponding to the Sentinel-1 SAR imagery. The performance of the five models was assessed and compared using the root-mean-square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (r). The results revealed that the GP model yielded the highest prediction performance (RMSE = 2.885, MAE = 1.897, and r = 0.808) and outperformed the other machine learning models. We conclude that the advanced machine learning models can be used for mapping soil salinity in the Delta areas; thus, providing a useful tool for assisting farmers and the policy maker in choosing better crop types in the context of climate change.

Satellite laser ranging to low Earth orbiters: orbit and network validation

Abstract: Satellite laser ranging (SLR) to low Earth orbiters (LEOs) provides optical distance measurements with mm-to-cm-level precision. SLR residuals, i.e., differences between measured and modeled ranges, serve as a common figure of merit for the quality assessment of orbits derived by radiometric tracking techniques. We discuss relevant processing standards for the modeling of SLR observations and highlight the importance of line-of-sight-dependent range corrections for the various types of laser retroreflector arrays. A 1–3 cm consistency of SLR observations and GPS-based precise orbits is demonstrated for a wide range of past and present LEO missions supported by the International Laser Ranging Service (ILRS). A parameter estimation approach is presented to investigate systematic orbit errors and it is shown that SLR validation of LEO satellites is not only able to detect radial but also along-track and cross-track offsets. SLR residual statistics clearly depend on the employed precise orbit determination technique (kinematic vs. reduced-dynamic, float vs. fixed ambiguities) but also reveal pronounced differences in the ILRS station performance. Using the residual-based parameter estimation approach, corrections to ILRS station coordinates, range biases, and timing offsets are derived. As a result, root-mean-square residuals of 5–10 mm have been achieved over a 1-year data arc in 2016 using observations from a subset of high-performance stations and ambiguity-fixed orbits of four LEO missions. As a final contribution, we demonstrate that SLR can not only validate single-satellite orbit solutions but also precise baseline solutions of formation flying missions such as GRACE, TanDEM-X, and Swarm.