Abstract

The rapid growing number of earth observation missions and commercial low-earth-orbit (LEO) constellation plans have provided a strong motivation to get accurate LEO satellite position and velocity information in real time. This paper is devoted to improve the real-time kinematic LEO orbits through fixing the zero-differenced (ZD) ambiguities of onboard Global Navigation Satellite System (GNSS) phase observations. In the proposed method, the real-time uncalibrated phase delays (UPDs) are estimated epoch-by-epoch via a global-distributed network to support the ZD ambiguity resolution (AR) for LEO satellites. By separating the UPDs, the ambiguities of onboard ZD GPS phase measurements recover their integer nature. Then, wide-lane (WL) and narrow-lane (NL) AR are performed epoch-by-epoch and the real-time ambiguity–fixed orbits are thus obtained. To validate the proposed method, a real-time kinematic precise orbit determination (POD), for both Sentinel-3A and Swarm-A satellites, was carried out with ambiguity–fixed and ambiguity–float solutions, respectively. The ambiguity fixing results indicate that, for both Sentinel-3A and Swarm-A, over 90% ZD ambiguities could be properly fixed with the time to first fix (TTFF) around 25–30 min. For the assessment of LEO orbits, the differences with post-processed reduced dynamic orbits and satellite laser ranging (SLR) residuals are investigated. Compared with the ambiguity–float solution, the 3D orbit difference root mean square (RMS) values reduce from 7.15 to 5.23 cm for Sentinel-3A, and from 5.29 to 4.01 cm for Swarm-A with the help of ZD AR. The SLR residuals also show notable improvements for an ambiguity–fixed solution; the standard deviation values of Sentinel-3A and Swarm-A are 4.01 and 2.78 cm, with improvements of over 20% compared with the ambiguity–float solution. In addition, the phase residuals of ambiguity–fixed solution are 0.5–1.0 mm larger than those of the ambiguity–float solution; the possible reason is that the ambiguity fixing separate integer ambiguities from unmodeled errors used to be absorbed in float ambiguities.

Highlights

  • Over the past two decades, the increasing number of satellites in Low Earth Orbits (LEOs) has found ever growing interest in space-based earth observations such as gravimetry [1,2,3], altimetry [4,5], radio occultation [6], and so forth

  • It can be found that over 90% WL and 93% NL ambiguity residuals are within 0.15 cycles, which further confirms the high reliability of WL and NL uncalibrated phase delays (UPDs) correction

  • Taking the LEO satellite’s latitude into consideration, we can recognize a potential correlation between the latitude change and periodic variation of orbit error: the LEO satellite shows inferior precise orbit determination (POD) accuracy in high latitude while the POD accuracy is relatively better in low altitude

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Summary

Introduction

Over the past two decades, the increasing number of satellites in Low Earth Orbits (LEOs) has found ever growing interest in space-based earth observations such as gravimetry [1,2,3], altimetry [4,5], radio occultation [6], and so forth. With the help of spaceborne Global Navigation Satellite System (GNSS) receivers, LEO orbits can achieve an accuracy of 2–5 cm using precise GNSS orbit and clock products in post processing [5,7]. Using the state-of-the-art near-real-time orbit and clock products, Montenbruck et al [11] demonstrated that the real-time reduced dynamic orbit of MetOp-A satellite could achieve an accuracy of around 5 cm. Montenbruck et al [19,30] performed post-processing POD for Sentinel-3 and Swarm satellites with CNES/CLS IRC products and reported about 30–50% orbit accuracy improvements compared with the float solution. Allende-Alba et al [31] demonstrated that ZD AR could improve the baseline precision in LEO satellite relative positioning In this contribution, we focus on improving the performance of real-time LEO kinematic POD through the ZD AR method.

Observation Mode
Zero-Differenced Ambiguity Resolution
POD Strategies
Data Sets
Results
Ambiguity Fixing Results
POD Results
Discussion
Full Text
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