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GNSS Constellation Specific Monthly Analysis Summary: April 2024

Jun 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 the satellite Timing Group Delay (TGD)/ Broadcast Group Delay (BGD) parameters in terms of their applicabilities.

Analyzed Parameters for March, 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. Satellite Hardware Delay (TGD/BGD): The hardware delays originating from the analog and digital parts of the satellite’s transmission. Mostly, the time difference between the transmitted RF signal,measured at the transmitting antenna, and the signal at the output of the onboard frequency source.

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): Satellite Hardware Delay (TGD/BGD and Precise DCB)

(Dhital et.al, 2024) discussed briefly on the TGD/BGD parameters transmitted by the GNSS satellites. In this month’s issue, the compatibility of such parameters with the post-processed and highly precise Differential Code Bias (DCB) products is discussed. The one-to-one comparison of TGD/BGD and DCB values does not make much sense as different conventions are used in the respective estimation of broadcast values and post-processed DCB. In the network processing, the functional model of GNSS observations suffers from a singularity as unique solution to the estimable parameter is not available. As explained in (Montenbruck et.al, 2014 a), the clock offset parameters and code bias parameters cannot be uniquely estimated in the same estimation process. However, when two signals are combined to the same satellite and receiver pair, the clock offset parameters can be removed. Following this approach, the estimation of satellite plus receiver biases for all network stations and satellites is possible. The next step is to separate the satellite code bias and receiver code bias.

since a bias common to all satellites cannot be distinguished from a corresponding bias common to all receivers. In other words, if a constant is added to all satellite bias in the observation model, then the same constant can be added to all the receiver bias, to keep the observed value unchanged. Therefore, for a realistic estimation of satellite biases a constraint needs to be imposed on the equations of least square estimation which removes the rank-deficiency/singularity. There are different ways to apply the constraint, but commonly used approaches are to fix one calibrated receiver (mostly used in control segment of the GNSS) and to impose constellation zero-mean condition (as used in post-processed precise bias estimation). This also means the estimated satellite biases are relative to the used constraint, which is very important to consider while analyzing the TGD and DCB values. If zeromean constellation condition is used

With this approach, an attention must be paid in the event of status change in the constellation (i.e., removal/addition of satellites) as this renders a systematic offset. This effect is monitored for Galileo constellation as shown in Figure f (a). However, the linear dependencies of bias and clock offset parameters renders no impact in the positioning solution as the receiver clock offset absorbs such systematic offset common to all satellites. For the analysis shown in the subsequent plots, the precise products from Chinese Academy of Sciences (CAS) are used for the comparison and days of year between 021 and 121, 2024 are taken. Note that, CAS DCB products are not available in the ftp for days 001 to 020 and day 085.

As both broadcast BGD and CAS precise DCB for Galileo are referenced to the zero-mean constellation constraint, a direct comparison shall also suffice. But the objective here is to validate the above-mentioned conventions with the data. As such, both broadcast BGD and CAS DCB are realigned towards the zero-mean constellation constraint (the daily mean of constellation is removed from individual satellite). It is clear from Figure f (a)(bias without alignment to the convention) that Galileo broadcast BGD has a systematic offset after day of year around 72 w.r.t the precise DCB. What this means is that there was a potential change in the satellites used in the Galileo mission control segment procedures. As per Galileo constellation status (i.e., NAGU), Galileo SAT GSAT0104 was decommissioned from around that time. When analyzed separately (not shown in Figure), the CAS DCB products show consistent behavior referenced to zero-mean constellation. In the same Figure f (a), the comparison between BGD and DCB, where both dataset are aligned to the reference constraint, shows better consistencies without any noticeable shifts. The RMS (or the standard deviation in this case as the mean value is removed) is 0.7 ns over the analyzed period.

Similar approach is carried out for Beidou 3 satellites, where the broadcast TGD1 values are realigned to the zero-mean condition of all available Beidou satellites. The result (Figure f (b)) shows RMS value of 1.10 ns over the analyzed period. Due to different calibration strategy used for TGD1 and CAS DCB estimators, this value shows only a rough indication and systematic offsets may still exist.

As for GPS constellation, the noticeable shift of TGD parameter in PRN 1 (blue line, the shifted value after day of year 113 is isolated in the bottom of plot) is observed in Figure f (c). It shows the bias value switches from around 5 ns to around -19 ns. The GPS constellation status (i.e., NAGU advisory number “2024020”) reports that on approximately 22 April (day of year 113) satellite vehicle number SVN49 resumes transmitting L-band in PRN01 and advises not to use PRN01 until further notice. In GPS control segment, calibrated reference receivers are used to fix the rank deficiency in network estimation of TGD and this is why only PRN01 has shifted value without impacting other satellites. In terms of broadcast BGD/TGD, there are no other significant jumps/shift in all GNSS satellites for the month of April. For recap, the values for TGD/BGD are either calibrated and uploaded to the satellite or estimated as a part of the mission control activities and then uploaded to the satellite with varying temporal resolutions (Wang et.al, 2019). This indicates the TGD/ BGD values are slowly varying.

There as an additional step not explained above which relates to the frequency scaling factors for the respective DCB signal combinations. As the broadcast satellite clock offset is referenced to the linear combination of signals, single frequency observational model shall consider the DCB parameter in the model. Otherwise, the satellite clock inconsistency will propagate into the positioning solution. Similar consideration is needed if TGD is used instead of DCB (which is available with larger latency) in the single frequency modeling. When comparing these two approaches (Guo et.al, 2015), the relationship between TGD and DCB can be derived as:

Here, the frequency scaling factor for two signals with frequencies f1 and f2 is:

Monthly Performance Remarks:
1. Satellite Clock and Orbit Accuracy:
• For GPS, the satellite clock and orbit accuracy shows similar performance as in March 2024. There were couple of satellite outages and NANU and removed from the analysis. GPS PRN 17 had an unusable status on day of year 094 and 095. G01 is removed completely in the analysis. G21 had moderately large clock errors from day 108 to 115. It was included in the analysis.
• For Galileo, all parameters showed consistent performances.
• For GLONASS, the performance looked similar to the past months. Satellite R07 seemed maneuvering from day 106 to day 111 bad orbit on day 106. Satellites R09 and R11 have slightly degraded orbits from day 113 to 121.
• For BDS and QZSS, the performance looks very much the same as in the past. For QZSS, there are days with better orbit quality and some days with degraded performance. On day 121, QZSS J02 had a very large satellite clock offset jump.
• For IRNSS, the notable difference in this month’s performance is the inconsistent URA for I06 satellite. There were a varying confidences in the range accuracy for I06.
2. UTC Prediction (GNSS-UTC): Galileo constellation is more stable within 2.5 ns in the GNSS-UTC prediction. In March, 2024, the values ranged from 1 ns to 9 ns.

References

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 multi-GNSS 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

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

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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