Effect of Ionospheric Scintillation on Precise Positioning Solutions in Vietnam

Journal of Science & Technology 139 (2019) 068-072 
68 
Effect of Ionospheric Scintillation on Precise Positioning Solutions 
in Vietnam 
Hoang Van Hiep*, Nguyen Duc Tien, La The Vinh 
Hanoi University of Science and Technology, No. 1, Dai Co Viet, Hai Ba Trung, Hanoi, Viet Nam 
Received: July 03, 2019; Accepted: November 28, 2019 
Abstract 
The relative positioning applications can reach cm-level accuracy of positioning due to the use the very precise 
but ambiguous carrier phase observations instead of pseudorange ones used in conventional absolute 
positioning approach. These applications, however, are very sensitive to the irregular variation and 
disturbances in the ionospheric delay. Vietnam locates at a low-latitude region near the equator where having 
many irregular variations in ionosphere. In addition, here is one of the most affected region if any scintillation 
occurs. In this study, we first propose a software-based receiver to detect the ionospheric scintillation in 
Vietnam. After detecting the scintillation, we investigate the impact of the scintillation index to the precise 
positioning solutions. For scintillation detection, we compute 𝜎𝜎𝜙𝜙, a parameter to quantify the scintillation index. 
To investigate the effect of scintillation, we compare the results of RTK solutions in two scenarios: no 
scintillation and scintillation. Hopefully, these results will contribute valued information to GNSS research 
community in Vietnam. 
Keywords: Ionosphere, scintillation, GNSS, GPS 
1. Introduction1 
As we know, the atmosphere around the earth 
affects the travelling speed of the GNSS signal and 
causes measurement errors. Thus, the ionosphere layer 
causes the code in the GNSS signal delay but the 
carrier phase advance. This strongly influences on the 
precision of the GNSS receivers. In particular, a rapid 
fluctuation of radio-frequency signal phase and/or 
amplitude, generated as a signal passes through the 
ionosphere, is called scintillation. Theoretically, 
scintillation parameters can be extracted from GNSS 
signal by a receiver because of spread spectrum 
properties of the signal, the receiver can still do track 
the signal through disturbances even when the GNSS 
signal are themselves affected by the scintillation. 
There are some applications, however, such as 
surveying where carrier phase measurement are used, 
in which a strong scintillation may easily disrupt 
operational activities. Monitoring and/or further 
modeling the ionosphere layer is therefore a 
mandatory in the field of GNSS. 
Vietnam is located near the equator, at a low-
latitude region, where many strong scintillations may 
happen in a long period. Many related works 
investigated the ionosphere behavior via received GPS 
signal in Vietnam during a long period, from three to 
five years. The authors focus on determining and 
* Corresponding author: Tel.: (+84) 944.840.301 
Email: hiep.hoangvan@hust.edu.vn 
evaluating the total electronic content (TEC) variations 
[1-3]. The experimental results indicated that 
scintillations in Vietnam often happen at the time of 
season changing such as vernal equinox/autumnal 
equinox, at the time of strong solar activity, i.e., 
changing from day to night and vice versa. Those 
researches, however, used a commercial high cost GPS 
receiver for S4 and TEC logging. In this study, we 
propose to implement a software defined receiver 
(SDR) with extremely low cost compared to a 
professional one but is able to compute scintillation 
indexes. 
Related works can be divided into following main 
categories: 
• TEC characterization [1-3], 
• Ionospheric scintillation monitoring [4-7], 
• Ionosphere modeling [8-10] 
Most popular researches in low-latitude region 
including Vietnam just focused on investigating the 
variation of TEC during special time like season 
changing, day changing, magnetic storm, etc. using 
commercial hardware receiver. However, no 
scintillation detection method has been proposed. In 
high-latitude and mid-latitude region, several 
ionosphere models have been proposed such as the one 
in EGNOS system [11] or in WAAS system [12]. 
Journal of Science & Technology 139 (2019) 068-072 
69 
There are few studies on ionosphere modeling in low-
latitude region though. 
In the surveying field, in Vietnam, users typically 
use post processing method for precise positioning. In 
this method, raw GNSS satellite measurements are 
simultaneously collected and stored at the rover and 
reference stations for processing post-mission. The 
problem is that users may not know the quality of the 
GNSS signal at the time of data grabbing, if a strong 
scintillation occur during the process of data 
collecting, all the received data might be useless. 
Motivated by above reasons, we propose in this 
work a monitoring system which is able of: (1) 
computing scintillation index in real-time for detecting 
the moment of scintillation occur; (2) capturing raw 
GNSS data whenever a scintillation happens; and (3) 
investigate the effect of scintillation index on precise 
positioning solutions, this helps us to confirm whether 
the relative positioning can work or not in some 
scintillation conditions in Vietnam. We believe that 
our proposed system can be very helpful to GNSS 
users in Vietnam, especially for users in the surveying 
field. 
 The remaining of our paper is organized as 
following: in section 2, we give a detail description of 
our method and preliminary results, conclusions are 
drawn in section 3. 
2. The proposed method and results 
Figure 1 shows the architecture of our proposed 
method. We develop a software receiver to detect the 
scintillation. Two modules, a scintillation index 
calculation module and a scintillation detection 
module, are added into a common SDR. As we know, 
ionospheric scintillations are rapid fluctuations in 
received signal amplitude and phase. In this work, we 
study the effect of scintillation on the phase of signal. 
In order to investigate the impact of the 
scintillation on precise relative positioning, we grab 
raw data at two stations simultaneously, a base station 
and a rover station in order to use RTK post processing 
latter. The position of the base station is known in 
advance, whereas the position of the rover must be 
computed. We proposed to use SDR at the base station 
to compute scintillation index and extract the 
scintillation condition. For the rover station, we use a 
professional receiver to grab the data. 
2.1. Scintillation detection 
To detect the scintillation, in this study, we 
compute the 𝜎𝜎𝜙𝜙, 𝜙𝜙60 in particular, a parameter to 
evaluate the scintillation. After the tracking phase of 
software receiver, we can get the phase error, in an 
integrated time, we can compute the new carrier phase 
as follows: 
𝜑𝜑𝑛𝑛𝑛𝑛𝑛𝑛 = 2𝜋𝜋𝑓𝑓𝐷𝐷𝑇𝑇𝐼𝐼 + 𝜑𝜑𝑜𝑜𝑜𝑜𝑜𝑜 + 𝜑𝜑𝑛𝑛 (1) 
where: 𝑓𝑓𝐷𝐷 is the Doppler shift caused by relative 
movement between a satellite and the receiver, which 
can be defined as: 𝑓𝑓𝐷𝐷 = 𝑓𝑓𝑟𝑟 − 𝑓𝑓𝑆𝑆, where: 𝑓𝑓𝑟𝑟 is the 
frequency of the received signal and 𝑓𝑓𝑆𝑆 is the 
frequency of the sinusoid generated by local sinusoid 
signal generator; 𝑇𝑇𝐼𝐼 is the integrated time; 𝜑𝜑𝑛𝑛 is the 
phase error – one of the output of the tracking loop; 
𝜑𝜑𝑜𝑜𝑜𝑜𝑜𝑜 is the carrier phase of the last integrated time. The 
new carrier phase will then feedback to the local 
sinusoid signal generator. 
To compute the 𝜎𝜎𝜙𝜙, the carrier phase is first 
sampled at 50 Hz. Next, it is de-trended by applying a 
6th order high pass Butterworth filter with the cut off 
frequency of 0.1Hz to remove all the fluctuations 
introduced by other factors but not the scintillation 
such as multipath, satellite clock error, etc. [6]. Finally, 
the phase fluctuation, i.e., 𝜎𝜎𝜙𝜙 or the phase scintillation 
indicator is realized as: 
𝜎𝜎𝜙𝜙 = 𝑠𝑠𝑠𝑠𝑠𝑠(𝜑𝜑𝑛𝑛𝑛𝑛𝑛𝑛) (2) 
in which, std is the standard deviation, normally we 
evaluated for 1 minute, in such case the 𝜎𝜎𝜙𝜙is called 
𝜙𝜙60. 
To detect the scintillation, we simply use a 
threshold, 𝜃𝜃. If 𝜙𝜙60 exceeds 𝜃𝜃, a scintillation occurs 
otherwise there is no scintillation. In this study, the 
value of 𝜃𝜃 was chosen as 0.3 by experiments. 
Fig. 1. Proposed method architecture
Frontend Signal Acquisition Signal Tracking Navigation Data Extraction PVT Computation
Scintillation Index 
CalculationSDR
Base Station Raw 
Data Logging
Base station antenna
Rover station antenna
Scintillation Detection
Rover Station 
Raw Data 
Logging
Professional 
Hardware Receiver
RTK Post Processing
Evaluation Module
Journal of Science & Technology 139 (2019) 068-072 
70 
2.2. Scintillation monitoring results 
To confirm the accuracy of the 𝜎𝜎𝜙𝜙 computation by 
the proposed method, we utilized dataset of JRC [13] 
who is one of our laboratory’s cooperators in the field 
of GNSS. The dataset of JRC is grabbed on April 09th, 
2013. Figure 2 shows 𝜙𝜙60 values of our proposed 
method, dot-blue line, compare to those of JRC 
receiver for three separated satellites, PRN 1, PRN 7, 
and PRN 8. We can see that our results and JRC‘s ones 
are fitted to each other. This confirms that our 𝜙𝜙60 
computation is precise and accuracy. 
After confirming the accuracy of phhi60 
computation. We conduct an experiment with our own 
received data, in particular we recorded data for 20 
minutes started from 16h20 on April 19th, 2017 by 
using SiGe GN3Sv.3 frontend. Since the elevation 
angle between the receiver’s antenna and a satellite 
may affect to the value of 𝜙𝜙60, we filter out satellites 
which have elevation angel smaller than 20 degree. All 
visible satellites are shown in Fig. 3. Figure 4 shows 
the results of the PRN 7 and PRN 8 respectively. We 
can see that there was a weak scintillation with the 
satellite 8 and a strong scintillation occur with the 
satellite 7. In particular, the values of 𝜙𝜙60 for PRN 7 
are always higher than a pre-defined threshold, i.e., 0.3 
in our experiments. These results prove the ability of 
scintillation detection of our software receiver. 
Fig. 2. JRC dataset: 𝜙𝜙60 values for PRN 1, PRN7, and 
PRN8 of our method (blue – highpass detrending), 
compare to JRC receiver (red). 
Fig. 3. All visible satellites with recorded data on April 
19th, 2017. 
Fig. 4. NAVIS dataset: 𝜙𝜙60 values for PRN7, and 
PRN8 with the data received on 19/04/2017 at the 
NAVIS center, Hanoi, Vietnam. 
220,900 221,000 221,100 221,200 221,300 221,400 221,500 221,600 221,700 221,800 221,900 222,000
0
0.2
0.4
0.6
0.8
1
1.2
GPS TOW (s)
R
ad
ia
n
Phi60 PRN 1
sdr-soft
jrc
220,900 221,000 221,100 221,200 221,300 221,400 221,500 221,600 221,700 221,800 221,900 222,000
0
0.2
0.4
0.6
0.8
1
Ra
di
an
GPS TOW (s)
Phi60 PRN 7
220,900 221,000 221,100 221,200 221,300 221,400 221,500 221,600 221,700 221,800 221,900 222,000
0
0.2
0.4
0.6
0.8
1
GPS TOW (s)
R
ad
ia
n
Phi60 PRN 8
sdr-soft
jrc
318,000 318,200 318,400 318,600 318,800 319,000 319,200
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
GPS TOW (s)
R
ad
ia
n
Phi60 PRN 7
sdr-soft
318,000 318,200 318,400 318,600 318,800 319,000 319,200
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
GPS TOW (s)
R
ad
ia
n
Phi60 PRN 8
sdr-soft
PRN: 7 
PRN: 8 
PRN: 1 
PRN: 7 
PRN: 8 
Journal of Science & Technology 139 (2019) 068-072 
71 
In addition, to prove the concept that the 
scintilation condition is different among different 
lattitudes, we compare scintillation indexes including 
𝜙𝜙60 and S4 computed at Hanoi, a low latitude region, 
i.e., ionosphere layer operates stronger and those at 
Norway, a high latitude region where ionosphere layer 
operates weaker. Figure 5 shows scintillation indexes 
comparison between Hanoi and Norway. For thorough 
comparison, CN0 and S4 are provided as well in the 
Fig. 5. It can be seen that the signal quality is quite 
good at both regions, the CN0 values are normally 
greater than 40 which indicates a good quality of 
received signal. Based on S4 and 𝜙𝜙60 values, the 
scintillation at low latitude region is obviously higher 
than that at high latitude region. 
2.3. Effect of ionospheric scintillation on precise 
positioning solutions in Vietnam 
After detecting scintillation, we evaluate the 
effect of the scintillation index on precise positioning 
solution. To do that, we compare the results of RTK 
solutions in two scenarios: #1 quiet or nominal 
condition (i.e., no scintillation) and #2 disturbed 
condition (scintillation). 
Table 1. Daily Statistic of Positioning Errors 
RMS E-W (cm) 
N-S 
(cm) 
U-D 
(cm) Fixed ratio 
#1 2.5 2.6 8 85% 
#2 55 88 127 24% 
(a) Scintillation index computed for data recorded at 
Hanoi. 
(b) Scintillation index computed for data recorded at 
Norway. 
Fig. 5. Scintillation index comparison between a low latitude and a high latitude area. 
(a) Quiet (no scintillation) condition (b) Scintillation condition 
Fig. 6. RTK positioning errors in E-W, N-S, and U-D directions. 
Journal of Science & Technology 139 (2019) 068-072 
72 
Table 1 shows the RMS for 3 directions (E-W, N-
S, and U-D) in centimeter as well as the fixed ratio of 
the RTK solutions in two conditions, the red one is for 
#2, scintillation condition. Figure 6 illustrates the 
positioning errors of 20-minute data for E-W, N-S, and 
U-D for #1, and #2 condition respectively. It can be 
seen that the RTK solution results in scintillation 
condition is much worse than those in quite case. In 
particular, the RMS for three directions are higher, the 
fixed ratio is significantly reduced, 24%. These results 
indicate that normal RTK solution could not work well 
in scintillation condition. This is theoretically clear 
because RTK solution use carrier phase measurements 
which are easily disrupted by scintillation. 
3. Conclusions 
In this paper, we have proposed a SDR to compute 
𝜎𝜎𝜙𝜙 as a parameter to detect the scintillation as well as 
studied the effect of scintillation on precise 
positioning. The SDR approach requires no high-cost, 
specific-designed hardware and thus is able to deploy 
on any personal computer. 
 However, our experiments with RTK solutions are 
now preliminary. In the future, we plan to do more 
thoroughly experiments to investigate the impact of 
scintillation on precise possitioning not only the RTK 
method but also the PPP (Presice Point Positioning) 
method. 
Nevertheless, we believe that our preliminary 
experimental results will contribute valued 
information to GNSS research community in Vietnam. 
Acknowledgement 
This research was supported by Hanoi University 
of Science and Technology under the contract number 
T2017-PC-168 and Ministry of Science and 
Technology under the project number 
NĐT.38.ITA/18. 
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