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Performance of BDS B1 frequency standard point positioningduring the main phase of different classes of geomagnetic storms inChina and its surrounding area

25 Jan 2021-Annales Geophysicae (Copernicus GmbH)-pp 1-16
TL;DR: In this paper, the performance of the BeiDou Navigation Satellite System (BDS) B1 frequency standard point positioning in China and its surrounding area during different classes of storms is investigated for the first time.
Abstract: . Geomagnetic storms are one of the space weather events. The radio signals transmitted by modern navigation systems suffer from the effects of storms which can degrade the performance of the whole system. In this study, the performance of BeiDou Navigation Satellite System (BDS) B1 frequency standard point positioning in China and its surrounding area during different classes of storms is investigated for the first time. The analysis of the results revealed that BDS B1 frequency standard point positioning accuracy was deteriorated during the storms. The probability of the extrema in the statistics of positioning errors during strong storms is the largest, followed by moderate and weak storms. The positioning accuracy for storms of a similar class is found not to be at the same level. The root mean square error (RMSE) in position for the different classes of storms could be at least tens of centimeters in the East, North and Up directions.

Summary (1 min read)

1 Introduction

  • A geomagnetic storm is defined as a period when the ring current gets intense enough to exceed the key threshold of the distur-10 bance storm time (Dst) index.
  • The disturbed condition of the ionosphere during geomagnetic storms is known as20 an ionospheric storm, which can have great effects on radio propagation dependent applications, especially for GNSS single– frequency users.
  • The accuracy of Real Time Kinematic (RTK) positioning could also be deteriorated during a strong geomagnetic storm (Jacobsen and Schäfer, 2012), and even during a weak storm at high latitudes (Andalsvik and Jacobsen, 2014).
  • Dst index can be used as a criterion to classify geomagnetic storms (Loethe authors and Prölss, 1997).
  • The related information, such as geodetic coordinates, receiver and antenna version, is shown in Table 3.

BIAS =<∆POSi >

  • The accuracy of BDS B1 frequency SPP solutions during the main phase of different classes of storms is analysed in this section.
  • As shown in the figures, the positioning errors increased to some extent during the main phase of different classes of storm.
  • It can be seen that there were large jumps in PDOP.
  • The main reason for the jumps in the positioning errors for the three stations (LHAZ, HKWS, HKSL) may be attributed to a comprehensive effect.
  • The vertical dark grey dotted line indicates the epoch of minimum Dst, the UT time of minimum The160 time range covered 10 days before and after the main phase day.

4 Conclusions

  • The performance of BDS B1 frequency SPP during the main phase of different classes of storms in China and its surrounding area was investigated.
  • Thirdly, the positioning accuracy may be influenced even in the recovery phase of storms.
  • The study needs to be extended with the arrival of solar cycle 25 and with the addition of more storm events.
  • Junchen Xue carried out analysis and prepared the paper.
  • The authors thank the anonymous referees for their valuable suggestions.

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Performance of BDS B1 frequency standard point positioning
during the main phase of different classes of geomagnetic storms in
China and its surrounding area
Junchen Xue
1
, Sreeja Vadakke Veettil
2
, Marcio Aquino
2
, Xiaogong Hu
1
, Lin Quan
3
, and Dun Liu
4
1
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China
2
Nottingham Geospatial Institute, University of Nottingham, Nottingham, UK
3
Beijing Institute of Tracking and Communication Technology, Beijing, China
4
China Research Institute of Radiowave Propagation, Qingdao, China
Correspondence: Junchen Xue (jcxue@shao.ac.cn)
Abstract. Geomagnetic storms are one of the space weather events. The radio signals transmitted by modern navigation
systems suffer from the effects of storms which can degrade the performance of the whole system. In this study, the performance
of BeiDou Navigation Satellite System (BDS) B1 frequency standard point positioning in China and its surrounding area during
different classes of storms is investigated for the first time. The analysis of the results revealed that BDS B1 frequency standard
point positioning accuracy was deteriorated during the storms. The probability of the extrema in the statistics of positioning5
errors during strong storms is the largest, followed by moderate and weak storms. The positioning accuracy for storms of a
similar class is found not to be at the same level. The root mean square error (RMSE) in position for the different classes of
storms could be at least tens of centimeters in the East, North and Up directions.
1 Introduction
A geomagnetic storm is defined as a period when the ring current gets intense enough to exceed the key threshold of the distur-10
bance storm time (Dst) index. Geomagnetic storms are induced by the intense and continuing interplanetary convection electric
field and the energy injection to the magnetosphere–ionosphere system (Gonzalez et al., 1994). The enhanced interplanetary
convection electric field is motivated by a constant southward interplanetary magnetic field (IMF) (Hori et al., 2005). The solar
wind carries the coronal magnetic field into the entire heliosphere, thus forming the IMF (Owens and Forsyth, 2013). Based
on the signatures in the magnetic field, a geomagnetic storm can be divided into three phases: initial, main, and recovery. The15
main phase is the principal characteristic of a geomagnetic storm (Gonzalez et al., 1994; Loewe and Prölss, 1997).
The largest global atmospheric effects can be activated by geomagnetic storms (Lastovicka, 1996). Storms can generate
disturbances in the ionosphere, which varies with the location of the region under consideration, local time (LT) of the geo-
magnetic storm onset and other parameters (Danilov and Lastovicka, 2001). The Equatorial Ionization Anomaly also responds
to the effects of storms (Sreeja et al., 2009). The disturbed condition of the ionosphere during geomagnetic storms is known as20
an ionospheric storm, which can have great effects on radio propagation dependent applications, especially for GNSS single–
1
https://doi.org/10.5194/angeo-2021-5
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c
Author(s) 2021. CC BY 4.0 License.

frequency users. These effects can usually be corrected by ionospheric models. For BeiDou Navigation Satellite System (BDS)
single–frequency users a Klobuchar–style ionospheric navigation model is applied for the corrections (BDS, 2013).
The performance of GNSS may be influenced by the effects of geomagnetic storms. During storms, carrier phase slips in the
Global Positioning System (GPS) signals may occur, which further results in losses–of–lock (LOL) (Rama Rao et al., 2009).25
Astafyeva et al. (2014) demonstrated that the density of GPS LOL events during the main phase of storms can increase to 0.25%
on L1 band and 3% on L2 band during super storms (Dst-250nT), and 0.15% on L1 and 1% on L2 during intense storms (-
250nT<Dst-100nT). Especially, the tracking performance of GPS receivers in the high latitudes was investigated for 2015 St.
Patrick’s day strong storm. The significant scintillation caused by the storm contributed to LOL on GPS L2 band but had little
influence on the tracking of GPS L1 signal (Jin and Oksavik, 2018). Kinematic GPS positioning could also be degraded during30
the geomagnetic storm induced ionospheric disturbances. The repeatability of kinematic positioning which were estimated by
a two–step approach based on double–difference L3 phase measurements reached 12.8, 8.1, and 26.1 cm in North (N), East
(E) and Up (U) directions respectively during the 2003 Halloween storm (Bergeot et al., 2011). The accuracy of Real Time
Kinematic (RTK) positioning could also be deteriorated during a strong geomagnetic storm (Jacobsen and Schäfer, 2012),
and even during a weak storm at high latitudes (Andalsvik and Jacobsen, 2014). Furthermore, positioning errors of network35
RTK and Precise Point Positioning (PPP) techniques increased rapidly during the 2015 St. Patrick’s day strong storm period
(Jacobsen and Andalsvik, 2016). Investigation was also performed on the effect of moderate and weak geomagnetic storms
on the performance of GNSS–SBAS in low latitude African region by using a SBAS emulator to simulate specific EGNOS
like messages. The SBAS performance in equatorial African regions showed a non–linear relationship with the geomagnetic
storm indices (Abe et al., 2017). Additionally, GPS instrumental biases, including receiver and satellite biases, are routinely40
estimated with the dual–frequency geometry–free combination. These computations can also be affected during geomagnetic
storms (Zhang et al., 2009).
Even though previous studies have revealed the effects of individual or several geomagnetic storms on the Earth’s upper
atmosphere and GNSS applications, few papers have studied the performance of BDS based applications during storms, es-
pecially during different classes of geomagnetic storms. As the ionospheric activity could be affected most likely during the45
geomagnetic storms, GNSS single–frequency users are supposed to be more obviously affected against other positioning modes
like PPP during those periods. In this study, the effects of different types of storms on the performance of BDS single frequency
standard point positioning, especially for the generally used B1 frequency users, is investigated comprehensively. In addition,
the differences in effects between separate storms are studied.
2 Methodology50
Dst index can be used as a criterion to classify geomagnetic storms (Loewe and Prölss, 1997). In this study, Dst indices were
extracted from combined omni files obtained from NASA database (https://omniweb.gsfc.nasa.gov). All storms in solar cycle
24 were analyzed and divided into three classes: Strong, Moderate and Weak. Table 1 states the threshold conditions applied
in the classification of storms (see (Gonzalez et al., 1994; Xue et al., 2020)).
2
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c
Author(s) 2021. CC BY 4.0 License.

Table 1. Thresholds implemented in the classification of geomagnetic storms
Type Dst (nT) T(hours)
Strong -100 3
Moderate -50 2
Weak -30 1
(typical substorm)
The basic strategy for selecting storms is that the Dst should be as minimum as possible and the duration of each storm55
should be more than 12 hours. To ensure that each storm was independent and not influenced by another storm, a condition
was applied that the Dst index for ten days before and after the main phase day must be greater than the minimum value for
each individual class of storms. Finally, ve cases were chosen for each class of storms from 2015 to 2018 (Xue et al., 2020).
The principal characteristic of a geomagnetic storm is its main phase (Loewe and Prölss, 1997). The main phase of storms
including the related Dst values, the start and end epoch, and the duration is presented in Table 2 (see (Xue et al., 2020)). TYPE60
means three classes of storms. MJD is the modified Julian date. The date with suffix 0 refers to the start epoch while suffix 1
suggests the end epoch. The meaning of suffix for Dst is same with the date. Duration represents the whole period of the main
phase.
BDS observations were collected from the chosen stations on the dates listed in Table 2. Those stations from MGEX network,
namely DAEJ, GMSD, JFNG, LHAZ, HKWS, and HKSL, are distributed in China and its surrounding area. The sampling65
interval is 30s. The related information, such as geodetic coordinates, receiver and antenna version, is shown in Table 3. The
last two columns show the dates when the hardware like receiver or antenna was changed or updated.
The data were processed in the kinematic mode of standard point positioning (SPP) using BDS single frequency pseudorange
observations. Considering the dispersive nature of the ionosphere, only B1 pseudorange was used here. The pseudorange
observation equation is illustrated as follows.70
B
1
= ρ + dt
r
dt
s
+ T + I
1
+ db
r1
db
s1
+ ε (1)
where, B
1
is BDS B1 pseudorange observation, ρ is the geometric range, dt
r
is the receiver clock error, dt
s
is the satellite
clock error, T is the tropospheric delay, I
1
is the ionospheric delay, db
r1
is the receiver differential code biase (DCB), db
s1
is
the satellite DCB, ε is the noise error.
A conventional option was set for the standard point positioning program. The satellite orbit and clock were computed from75
IGS navigation data. The tropospheric delays were derived using the Saastamoinen model. The ionospheric delays were cal-
culated by the broadcasted BDS navigation ionospheric model. Time group delays in the broadcast ephemeris were extracted,
converted and utilized to compute the satellite DCB. For each epoch, station coordinates and its receiver clock error were
3
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c
Author(s) 2021. CC BY 4.0 License.

Table 2. The main phase of different classes of geomagnetic storms from 2015 to 2018 (STR–Strong, MED–Moderate, MNM–Weak)
TYPE
MJD0
YEAR0
MON0
DAY0
DOY0
HOUR0
Dst0 (nT)
MJD1
YEAR1
MON1
DAY1
DOY1
HOUR1
Dst1 (nT)
Duration (hours)
STR
57098 2015 3 17 76 5 56 57098 2015 3 17 76 22 -223 17
57195 2015 6 22 173 6 13 57196 2015 6 23 174 4 -204 22
57302 2015 10 7 280 2 -9 57302 2015 10 7 280 22 -124 20
57375 2015 12 19 353 22 43 57376 2015 12 20 354 22 -155 24
58355 2018 8 25 237 8 19 58356 2018 8 26 238 6 -174 22
MED
57180 2015 6 7 158 19 24 57181 2015 6 8 159 8 -73 13
57273 2015 9 8 251 20 -2 57274 2015 9 9 252 12 -98 16
57406 2016 1 19 19 19 15 57407 2016 1 20 20 16 -93 21
57838 2017 3 26 85 22 15 57839 2017 3 27 86 14 -74 16
58064 2017 11 7 311 4 25 58065 2017 11 8 312 1 -74 21
MNM
57544 2016 6 5 157 8 32 57545 2016 6 6 158 6 -44 22
57716 2016 11 24 329 5 -12 57717 2016 11 25 330 5 -46 24
57784 2017 1 31 31 11 -5 57785 2017 2 1 32 9 -45 22
57920 2017 6 16 167 7 30 57920 2017 6 16 167 23 -31 16
58269 2018 5 31 151 21 5 58270 2018 6 1 152 19 -39 22
Table 3. Longitude, Latitude, Receiver and Antenna version information of stations
SITEN LATITUDE LONGITUDE RECEIVER ANTENNA YEAR DOY
DAEJ 36.40 127.37 TRIMBLE NETR9 TRM59800.00 2017 087
GMSD 30.56 131.02 TRIMBLE NETR9
TRM59800.00 2015 075
TRM41249.00 2017 311
TRM59800.00 2018 151
JFNG 30.52 114.49 TRIMBLE NETR9 TRM59800.00 2015 075
LHAZ 29.66 91.10 LEICA GR25 LEIAR25.R4 2016 157
HKWS 22.43 114.34
LEICA GR25
LEIAR25.R4
2015 353
LEICA GR50 2017 031
HKSL 22.37 113.93
LEICA GR25
LEIAR25.R4
2015 353
LEICA GR50 2016 329
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estimated with the Gauss–Newton least square method. The weight was set with the satellite elevation angle. The elevation
mask angle was set to 10
.80
As a result, the station coordinates in cartesian coordinate system were compared with the precise solutions in SINEX
files obtained from MGEX products. The related statistics were performed for the main phase period with indices such as
minimum (MIN), maximum (MAX), BIAS, and root mean square error (RMSE). The MIN and MAX represent the minimum
and maximum of the positioning errors for the three directions (East–E, North–N, Up–U). The BIAS and RMSE are computed
from the positioning errors for each component as well. The formulas are demonstrated as follows.85
MIN = minimum{P OS
i
}
MAX = maximum{P OS
i
}
BIAS =< P OS
i
>
RMSE =
q
< P OS
2
i
>
P OS
i
= P OS
ref,i
P OS
est,i
,i = 1, n (2)
Wherein, <> is the average of the variable, P OS
ref,i
is the precise solutions in SINEX files, P OS
est,i
is the solutions
obtained in this processing, n is the total number of samples.
3 Results and Discussions90
The accuracy of BDS B1 frequency SPP solutions during the main phase of different classes of storms is analysed in this
section. First, the positioning errors along the three directions for all the stations during a period of 3 days’ representative of
each class of storm are presented in Fig. 1–Fig. 3. The period shown in each of the figures covers three days before and after
the main phase of independent storms. The time range between two vertical red dashed lines is the whole main phase. The left
line indicates the start epoch of the main phase while the right one indicates the end epoch.95
As shown in the figures, the positioning errors increased to some extent during the main phase of different classes of storm.
The same happened in the recovery phase of the storm as well. For the strong storm shown in Fig. 1, the errors for ENU
directions present fluctuations during the main phase of the storm, especially in the U direction in which the errors could
be up to approximately 10 meters. In general, the positioning errors could reach about 2 meters in the E direction, about 5
meters in the N direction and about 11 meters in the U direction. However, in this case a larger degradation in positioning100
errors happened during the recovery phase. This can be attributed to the fact that the Dst values are lower and the geomagnetic
disturbance remained intense throughout. It is worth to notice that there are some sharp increases in the positioning errors
along the ENU directions of LHAZ station during the main phase of the storm. Nonetheless, there were no similar increases
observed for stations HKWS and HKSL which are located at lower latitudes. The increases were observed nearly at 1 LT and
lasted for about 30 minutes, thus indicating that this happened locally and temporarily. The time series of F10.7 cm radio105
5
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c
Author(s) 2021. CC BY 4.0 License.

Citations
More filters
Journal ArticleDOI
TL;DR: In this article , the authors investigated the impact of strong geomagnetic storms occurring in 2021 on positioning accuracy and found that the global 3D positioning accuracy of GPS + GPSK8, BDS + BDSK8 and BDGIM are 3.92 m, 4.63 m, and 3.50 m, respectively.
Abstract: The broadcast ionospheric model is one of the main methods for eliminating ionospheric delay errors for the Global Navigation Satellite Systems (GNSS) single-frequency users. GPS Klobuchar model (GPSK8) is the widely used broadcast ionospheric model for GPS, while BDS usually implements the BDS Klobuchar model (BDSK8) and BeiDou Global Broadcast Ionospheric Delay Correction Model (BDGIM). Geomagnetic storms may cause interference within the ionosphere and near-Earth space, compromising the accuracy of ionospheric models and adversely affecting the navigation satellite systems. This paper analyzes the static Standard Point Positioning (SPP) accuracy of GPS and BDS by implementing the broadcast ionospheric models and then investigates the impact of strong geomagnetic storms occurring in 2021 on positioning accuracy. The results show that the global 3D positioning accuracy (95%) of GPS + GPSK8, BDS + BDSK8, and BDS + BDGIM are 3.92 m, 4.63 m, and 3.50 m respectively. BDS has a better positioning accuracy in the northern hemisphere than that of the southern hemisphere, while the opposite is valid for GPS. In the mid-latitude region of the northern hemisphere, BDS + BDSK8 and BDS + BDGIM have similar positioning accuracy and are both better than GPS + GPSK8. The positioning accuracy after applying those three broadcast ionospheric models shows the superior performances of winter and summer over spring and autumn (based on the northern hemisphere seasons). With the exception of during winter, nighttime accuracy is better than that of daytime. The strong geomagnetic storm that occurred on the day of year (DOY) 132, 2021 has an impact on the positioning accuracy for only a small number of stations; however, the global average positioning accuracy is not significantly affected. The strong geomagnetic storms that occurred in DOY 307 and DOY 308 have a significant impact on the positioning accuracy of dozens of stations, and the global average positioning accuracy is affected to a certain extent, with some stations experiencing a serious loss of accuracy. Decreased degrees in positioning accuracy is proportional to the intensity of the geomagnetic storm. Of the 33 IGS Multi-GNSS Experiment (MGEX) stations worldwide, those located in the low and mid-latitudes are more significantly affected by the geomagnetic storms compared with higher latitudes. Evident fluctuations of the positioning errors existed during the strong geomagnetic storms, with an increase in extreme values, particularly in the up direction.

3 citations

References
More filters
Journal ArticleDOI
TL;DR: In this article, an attempt is made to define a geomagnetic storm as an interval of time when a sufficiently intense and long-lasting interplanetary convection electric field leads, through a substantial energization in the magnetosphere-ionosphere system, to an intensified ring current sufficiently strong to exceed some key threshold of the quantifying storm time Dst index.
Abstract: After a brief review of magnetospheric and interplanetary phenomena for intervals with enhanced solar wind-magnetosphere interaction, an attempt is made to define a geomagnetic storm as an interval of time when a sufficiently intense and long-lasting interplanetary convection electric field leads, through a substantial energization in the magnetosphere-ionosphere system, to an intensified ring current sufficiently strong to exceed some key threshold of the quantifying storm time Dst index. The associated storm/substorm relationship problem is also reviewed. Although the physics of this relationship does not seem to be fully understood at this time, basic and fairly well established mechanisms of this relationship are presented and discussed. Finally, toward the advancement of geomagnetic storm research, some recommendations are given concerning future improvements in monitoring existing geomagnetic indices as well as the solar wind near Earth.

1,963 citations


"Performance of BDS B1 frequency sta..." refers background in this paper

  • ...The 15 main phase is the principal characteristic of a geomagnetic storm (Gonzalez et al., 1994; Loewe and Prölss, 1997)....

    [...]

  • ...Table 1 states the threshold conditions applied in the classification of storms (see (Gonzalez et al., 1994; Xue et al., 2020))....

    [...]

  • ...Geomagnetic storms are induced by the intense and continuing interplanetary convection electric field and the energy injection to the magnetosphere–ionosphere system (Gonzalez et al., 1994)....

    [...]

  • ...The15 main phase is the principal characteristic of a geomagnetic storm (Gonzalez et al., 1994; Loewe and Prölss, 1997)....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors used the Dst index to identify more than 1000 storms which occurred in the time interval 1957 to 1993, using the minimum Dst value as an indicator, and classified the storms as weak (482), moderate (346), strong (206), severe (45), and great (6).
Abstract: The Dst index is used to identify more than 1000 storms which occurred in the time interval 1957 to 1993. Using the minimum Dst value as an indicator, we classify the storms as weak (482), moderate (346), strong (206), severe (45), and great (6). For each of these classes the mean time variation is determined. In contrast to the well-known study of Sugiura and Chapman [1960], the Dst minimum is used as a common reference epoch. This leads to much better agreement between the average and the typical storm behavior. We also find that the maximum ap and AE activity precedes the Dst minimum by 1 to 2 hours. Finally, we demonstrate that both sudden commencement and gradual commencement storms are associated with a distinct decrease in the Bz component of the interplanetary magnetic field.

369 citations

01 Jan 2001
TL;DR: A geomagnetic storm is a complex process: its various features act at dierent heights as mentioned in this paper, and at lower heights the role of ionization and photochemical processes increases due to shorter electron lifetimes.
Abstract: A geomagnetic storm is a complex process: its various features act at dierent heights. In the F2 layer the midlatitude eect is basically an ionospheric response to storm-induced changes in the neutral atmosphere, which are primarily a consequence of a strong Joule heating in the auroral thermosphere. At lower heights the role of ionization and photochemical processes increases due to shorter electron lifetimes. At the base of the F1 layer (160-170 km) the storm eect is almost absent. At

180 citations


"Performance of BDS B1 frequency sta..." refers background in this paper

  • ...Storms can generate disturbances in the ionosphere, which varies with the location of the region under consideration, local time (LT) of the geomagnetic storm onset and other parameters (Danilov and Lastovicka, 2001)....

    [...]

Journal ArticleDOI
TL;DR: Geomagnetic storm effects at heights of about 0-100 km are briefly reviewed in this article, with emphasis being paid to middle latitudes, particularly to Europe, and correlations with geomagnetic storms seem to reappear in the troposphere.

109 citations

Journal ArticleDOI
TL;DR: The 2015 St. Patrick's day storm was the first storm of solar cycle 24 to reach a level of "Severe" on the NOAA geomagnetic storm scale as discussed by the authors.
Abstract: The 2015 St. Patrick’s day storm was the first storm of solar cycle 24 to reach a level of “Severe” on the NOAA geomagnetic storm scale. The Norwegian Mapping Authority is operating a national real-time kinematic (RTK) positioning network and has in recent years developed software and services and deployed instrumentation to monitor space weather disturbances. Here, we report on our observations during this event. Strong GNSS (Global Navigation Satellite System) disturbances, measured by the rate-of-TEC index (ROTI), were observed at all latitudes in Norway on March 17th and early on March 18th. Late on the 18th, strong disturbances were only observed in northern parts of Norway. We study the ionospheric disturbances in relation to the auroral electrojet currents, showing that the most intense disturbances of GNSS signals occur on the poleward side of poleward-moving current regions. This indicates a possible connection to ionospheric polar cap plasma patches and/or particle precipitation caused by magnetic reconnection in the magnetosphere tail. We also study the impact of the disturbances on the network RTK and Precise Point Positioning (PPP) techniques. The vertical position errors increase rapidly with increasing ROTI for both techniques, but PPP is more precise than RTK at all disturbance levels.

105 citations

Frequently Asked Questions (2)
Q1. What are the contributions mentioned in the paper "Performance of bds b1 frequency standard point positioning during the main phase of different classes of geomagnetic storms in china and its surrounding area" ?

In this study, the performance of BeiDou Navigation Satellite System ( BDS ) B1 frequency standard point positioning in China and its surrounding area during different classes of storms is investigated for the first time. The probability of the extrema in the statistics of positioning 5 errors during strong storms is the largest, followed by moderate and weak storms. 

The study needs to be extended with the arrival of solar cycle 25 and with the addition of more storm events. Moreover, with the increase of BDS observation more comprehensive study on the performance of BDS single frequency SPP can be performed in near future. The authors thank the anonymous referees for their valuable suggestions.