GNSS Constellation Specific Monthly Analysis Summary: October 2024

The analysis performed in this report is solely his work and own opinion. State Program: U.S.A (G); EU (E); China (C) “Only MEO- SECM satellites”; Russia (R); Japan (J); India (I)

Narayan Dhital Actively involved to support international collaboration in GNSSrelated activities. He has regularly supported and contributed to different workshops of the International Committee on GNSS (ICG), and the United Nations Office for Outer Space Affairs (UNOOSA). As a professional employee, the author is working as GNSS expert at the Galileo Control Center, DLR GfR mbH, Germany

Introduction

The article is a continuation of monthly performance analysis of the GNSS constellation. Please refer to previous issues for past analysis. The time transfer method using GNSS pseudorange measurements is further analyzed in this month’s analysis. An example of the application of GNSS for on-board orbit determination and time synchronization in LEO missions is provided.

Analyzed Parameters for August, 2024

(Dhital et. al, 2024) provides a brief overview of the necessity and applicability of monitoring the satellite clock and orbit parameters.
a.. Satellite Broadcast Accuracy, measured in terms of Signal-InSpace Range Error (SISRE) (Montenbruck et. al, 2010).
b. SISREOrbit ( only orbit impact on the range error), SISRE (both orbit and clock impact), and SISREPPP (as seen by the users of carrier phase signals, where the ambiguities absorb the unmodelled biases related to satellite clock and orbit estimations. Satellite specific clock bias is removed) (Hauschlid et.al, 2020)
c. Clock Discontinuity: The jump in the satellite clock offset between two consecutive batches of data uploads from the ground mission segment. It is indicative of the quality of the satellite atomic clock and associated clock model.

d. URA: User Range Accuracy as an indicator of the confidence on the accuracy of satellite ephemeris. It is mostly used in the integrity computation of RAIM.
e. GNSS-UTC offset: It shows stability of the timekeeping of each constellation w.r.t the UTC.
f. Time Transfer and LEO Mission Application: The analysis shows the performance of kinematic orbit and satellite receiver clock determination for LEO missions.

Note:- for India’s IRNSS there are no precise satellite clocks and orbits as they broadcast only 1 frequency which does not allow the dual frequency combination required in precise clock and orbit estimation; as such, only URA and Clock Discontinuity is analyzed.

(f) Time Transfer

Time synchronization and precise orbit determination is crucial in Earth observation satellites, telecommunication satellites and broad band services and GNSS has significantly advanced their mission capabilities. The use of legacy GPS receivers like Blackjack, PODRIX, IGOR and TriG and oscillators has been well documented, especially in missions like SWARM, Sentinel, CHAMP and GRACE. The time synchronization is driven by the short-term and long-term stability of the oscillators and two of those are the Ultra-Stable Oscillator (USO) for a better short-term stability and the Oven Controlled Crystal Oscillator (OCXO) for a better long-term stability. The performance of such oscillators in above mentioned satellite missions are provided in the references (check at the end of this section). In this article, only a brief analysis is carried out with a real Satellite data to demonstrate the use case of GNSS based intersatellite time transfer. Figure f(1) shows the time synchronization accuracy for the SWARM mission (time link between SWARM A and SWARM B satellites) on October 1, 2024. This is based on the purely kinematic GNSS orbit & clock estimations that are referenced to the GPS timescale. There are various approaches and new innovative techniques regarding the high precision time link between satellites (check at the end of the section). In the SWARM mission, the oscillator is the OCXO and is integrated in the PODRIX GPS receiver. The comparison and mission specific usages between the OCXO and USO, particularly in terms of their stability and behavior, provides valuable insights into their performance in different conditions. Therefore, as an example, the satellite mission (Sentinel 6A and GRACE) using USO is analyzed as well (Figure f(2)). The stability of the oscillators tied to the GPS timescale are primarily driven by factors like the GPS estimation errors, the stability of the frequency oscillator itself, the systematic effects caused by relativistic effects or other factors, and stability of the real-time time reference. While the GPS estimation errors and the stability of the real-time time reference are key factors for the short-term stability, for the mid- and long-term stabilities, the behavior of the oscillator itself and the systematic effects play a more important role. In Figure f(2) the systematic effects are mainly coming from the effects of geophysical phenomena: the Southern Atlantic Anomaly (SAA) and relativistic effects. These systematic effects can significantly impact the performance of oscillators, especially in higher altitude missions and in inclinations that align the orbit with the SAA like Sentinel 6A, and in lower altitude missions closer to the Earth (like GRACE) where powerful relativistic effects are in action. In the plot, GRACE satellite clock offset is shown as free running clock which is not tied to a GPS timescale and as such has a linear trend. The behavior of the Sentinel 6A clock is also linear but the plot is based on the detrended data to focus on the period variations triggered by potential SAA and relativistic effects. A deeper analysis in this topic is found in references at the end of this section.

Most of the LEO missions are for Earth observations for which the precise location of the satellite instrument is critical. Furthermore, the on-board real-time clock estimation requires the precise knowledge of the orbits. The LEO based PNT services, for example, can benefit from the on-board precise orbit that can be used to tie the oscillator to GNSS timescale and use for LEO PNT signals as well. Therefore, a very short analysis is provided here focusing on capability of kinematic orbit determination using the dual-frequency code-only measurements with broadcast ephemerides. The Figure f(3) shows the orbit accuracy of the SWARM A satellite for October 1, 2024, in comparison to the precise science orbit. The advanced methods like PPP-AR and reduceddynamics provide even precise orbits.

The data for above analysis is retrieved from European Space Agency’s SWARM data portal (for SWARM satellite data), COSMIC data center (for GRACE data) and Copernicus Hub (for Sentinel data, accessed in 2023).

All important papers and product information used above analysis are listed here, providing the direct access sources:
1. Examples on the effects of SAA: https://www.tandfonline.com/doi/full /10.1080/10095020.2021.1917310#d 1e6103 https://www.sciencedirect.com/science/ article/abs/pii/S0273117716305282
2. Different methods of Time Transfer with LEO satellite (for inter-satellite link) using GNSS: https://navi.ion.org/content/ navi/71/3/navi.659.full.pdf
3. Overview of various GNSS receivers used in LEO missions: Overview of Space-Capable Global Navigation Satellite Systems Receivers: Heritage, Status and the Trend towards Miniaturization
4. Performance of USOs and OCXOs: https://www.tandfonline.com/doi/full/1 0.1080/10095020.2021.1917310 https://www.tandfonline.com/doi/ful l/10.1080/10095020.2021.1917310

Monthly Performance Remarks:

1. Satellite Clock and Orbit Accuracy:
▪ For Galileo, the performance looked similar to the past months. There is, however, a slight degradation in the orbit quality, hence, impacting the overall SISRE. GPS constellation provided several intermittent clock jumps, without drastic impact on the SISRE, that require further analysis and will be a part of next month’s issue.
▪ For GLONASS, the overall performance looked similar to last month
▪ For BDS and QZSS, the performance looks very much the same as in the past.
▪ For IRNSS, I06 has the poorest performance in terms of URA and satellite clock jumps.

2. UTC Prediction (GNSS-UTC):
▪ All constellations show better stability in comparison to previous months.

References

Alonso M, Sanz J, Juan J, Garcia, A, Casado G (2020) Galileo Broadcast Ephemeris and Clock Errors Analysis: 1 January 2017 to 31 July 2020, MDPI

Alonso M (2022) Galileo Broadcast Ephemeris and Clock Errors, and Observed Fault Probabilities for ARAIM, Ph.D Thesis, UPC

Cao X, Zhang S, Kuang K, Liu T (2018) The impact of eclipsing GNSS satellites on the precise point positioning, Remote Sensing 10(1):94

Dhital N (2024) GNSS constellation specific monthly analysis summary, Coordinates, Vol XX, Issue 1, 2, 3, 4

Hauschlid A, Montenbruck O (2020) Precise real-time navigation of LEO satellites using GNSS broadcast ephemerides, ION

Guo F, Zhang X, Wang J (2015) Timing group delay and differential code bias corrections for BeiDou positioning, J Geod,

IERS C04 (2024) https://hpiers.obspm.fr/ iers/eop/eopc04/eopc04.1962-now

IGS (2021) RINEX Version 4.00 https://files.igs.org/pub/data/ format/rinex_4.00.pdf

Li M, Wang Y, Li W (2023) performance evaluation of realtime orbit determination for LUTAN-01B satellite using broadcast earth orientation parameters and multi-GNSS combination, GPS Solutions, Vol 28, article number 52

Li W, Chen G (2023) Evaluation of GPS and BDS-3 broadcast earth rotation parameters: a contribution to the ephemeris rotation error Montenbruck O, Steigenberger P, Hauschlid A (2014) Broadcast versus precise ephemerides: a multi-GNSS perspective, GPS Solutions

Liu T, Chen H, Jiang Weiping (2022) Assessing the exchanging satellite attitude quaternions from CNES/CLS and their application in the deep eclipse season, GPS Solutions 26(1)

Montenbruck O, Steigenberger P, Hauschlid A (2014) Broadcast versus precise ephemerides: a multiGNSS perspective, GPS Solutions

Montenbruck O, Hauschlid A (2014 a) Differential Code Bias Estimation using Multi-GNSS Observations and Global Ionosphere Maps, ION

Steigenberger P, Montenbruck O, Bradke M, Ramatschi M (2022) Evaluation of earth rotation parameters from modernized GNSS navigation messages, GPS Solutions 26(2)

Sylvain L, Banville S, Geng J, Strasser S (2021) Exchanging satellite attitude quaternions for improved GNSS data processing consistency, Vol 68, Issue 6, pages 2441-2452

Walter T, Blanch J, Gunning K (2019) Standards for ARAIM ISM Data Analysis, ION

Wang N, Li Z, Montenbruck O, Tang C (2019) Quality assessment of GPS, Galileo and BeiDou-2/3 satellite broadcast group delays, Advances in Space Research

Wang J, Huang S, Lia C (2014) Time and Frequency Transfer System Using GNSS Receiver, Asia-Pacific Radio Science, Vol 49, Issue 12

https://cggtts-analyser.streamlit.app

Note: References in this list might also include references provided to previous issues.

Data sources and Tools:

https://cddis.nasa.gov (Daily BRDC); http://ftp.aiub.unibe.ch/ CODE_MGEX/CODE/ (Precise Products); BKG “SSRC00BKG” stream; IERS C04 ERP files

(The monitoring is based on following signals- GPS: LNAV, GAL: FNAV, BDS: CNAV-1, QZSS:LNAV IRNSS:LNAV GLO:LNAV (FDMA))

Time Transfer Through GNSS Pseudorange Measurements: https://elearning.bipm.org/login/index.php Allan Tools, https://pypi.org/project/ AllanTools/gLAB GNSS, https:// gage.upc.edu/en/learning-materials/ software-tools/glab-tool-suite.