GNSS


GNSS Constellation Specific Monthly Analysis Summary: May 2024

Jul 2024 | No Comment

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. In this month’s issue, there is an additional monitoring of URA in the context of RAIM and Advanced RAIM (ARAIM).

Analyzed Parameters for May, 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-In-Space Range Error (SISRE) (Montenbruck et. al, 2010).
b. SISRE-Orbit ( only orbit impact on the range error), SISRE (both orbit and clock impact), and SISRE-PPP (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. URA for ARAIM: URA plays a important role in the realization of ARAIM. Together with the SISRE, it allows characterization of the system behavior and determination of service

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) URA Statistics and Applications in RAIM/ARAIM

ARAIM utilizes a variety of signals from multiple satellite constellations, which inherently increases the chance of satellite faults compared to the traditional GPS-only RAIM. An essential aspect of ARAIM is its capability to manage several satellite faults simultaneously, accomplished through the use of Integrity Support Messages (ISM). Consequently, it’s vital for GNSS constellation service providers to work together closely and effectively to guarantee the reliability of ISM. Moreover, there may be varying perspectives among different providers regarding the choice of ISM parameter values. The ISM values have to be carefully evaluated based on the constellation performance data over a longer period of time. A basic overview on the applicability of broadcast URA to execute such evaluation is analyzed in the following paragraphs.

(Walter, et.al, 2019). URA plays a crucial role in the implementation of RAIM and ARAIM. In the traditional RAIM, URA is used for fault detections and for a faultfree case, it represents the zero-mean overbounding Gaussian for both integrity and accuracy computation. Different to it, the ARAIM uses separate zero-mean overbounding Gaussian (together with a

inflation factor, K, is computed as 4.42 (this can be reduced to 4.17 with new Psat= 10-5). The conceptual computation of the K value is provided in the literature (Walter, et.al, 2019). The K factor along with the URA value for each satellite provides a threshold to compare against the corresponding SIS error (as similar to the SISRE computed in this monthly analysis). If the SIS error is above the threshold, then there is a faulted event not captured by the system. The historical data for each constellation can be used to compute the Psat and Pconst (as of now, it is 10-8) and 10-4) for GPS and Galileo, respectively) based on the total faults detected over the given time period. The longer the time period, the better is the estimation of the probabilities. As such, both, SISE (similar to SISRE computed in this monthly analysis report but as instantaneous value and worst user location) and URA are very critical parameters for understanding the probabilities of fault events for each GNSS constellation. In this monthly issue, only an overview of the URA distribution for each constellation is provided. It can be observed in figures (f (1)- f (4)) that each constellation has satellites with varying URA values other than the designated standard accuracy. This indicates that there could be a potential fault even when the satellite is set to healthy and the broadcast validity is ok, and if the existing empirical analysis for past years (Alonso, et.al, 2019, 2020) is considered, for GPS and Galileo, the probability of single satellite fault is better than 10-5)/hour/ sat. This corresponds to the K factor of 4.17. For other constellations, similar approach can be used to compute the probabilities for the service commitment. This is also a testament to the necessity of analyzing the behavior of URA together with the SISE (in this analysis only 5 months data is seen but in the mentioned literature, they give analysis of longer time period).

The target of the ARAIM concept is to enable aviation integrity services from RNP 0.3 (H-RAIM) upto LPV-200 (V-RAIM). Rather than broadcast the conservative URA as is the case in RAIM, the ARAIM concept expects, in addition to handling fault cases with Psat and Pconst, relaxing the URA values by providing a bias term and the multiplier terms to separately bound the SIS accuracy and integrity. In doing so, the availability and integrity can be maintained to meet the required specifications of from RNP 0.3 up to LPV-200. The deployment of initial ARAIM is planned for 2025.

For Beidou, all satellites consistently broadcast URA value of 2.0 m 100 % of the time and as such, the plot was not deemed necessary. For Glonass, the URA value is not available in the RINEX broadcast message file. There will be an attempt in the future to combine the URA overview provided in this month’s issue with the SISE analysis and empirically derive the probability of satellite fault and constellation fault.

Monthly Performance Remarks:
1. Satellite Clock and Orbit Accuracy:
• For GPS, the satellite clock and orbit accuracy shows similar performance as in April 2024. There were couple of satellite outages and NANU and removed from the analysis. As in previous months, GPS PRN 17 had couple of unusable status on day 138. G07 had bad clocks during day 146 – 150.
• For Galileo, all parameters showed consistent performances. E11 had relatively large clock jump between consecutive batches of upload on day 122.
• For GLONASS, the performance looked similar to the past months. There were couple of satellites unusable which were removed in the analysis.
• For BDS and QZSS, the performance looks very much the same as in the past. For QZSS, there were couple of advisories to not use specific satellites. Example, J02 was not available on day 122. There were days with better orbit quality and some days with degraded performance. BDS has announced routine maintenance activities in its constellation from 31st May, 2024.
• For IRNSS, the notable difference in this month’s performance is the URA for all satellites. There were not a varying confidence in the range accuracy as in the previous months.

2. UTC Prediction (GNSS-UTC):
• Not much difference in comparison to the last month analysis but Glonass showed slightly consistent values.

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 real-time orbit determination for LUTAN-01B satellite using broadcast earth orientation parameters and multiGNSS 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 multiGNSS 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

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

Data sources:

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))

 

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