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Precise Positioning by smartphones is in the early steps. In this presentation, an overview of this novel subject is discussed and possible future works are introduced.
Precise Positioning By
Amir Allahvirdi-Zadeh
Curtin University
In this presentation…
Introduction of Precise positioning by smartphones
Problems of positioning with Smartphones
Review of the related projects
Future works
2Amir Allahvirdizadeh - Curtin University
What if we had centimetre accuracy in phones?
Google (May 2016): Access to Code and
Phase measurements is possible now!
Precise positioning by smartphones:
rapid mapping
emergency situations
3Amir Allahvirdizadeh - Curtin University
GNSS logger
Geo++ RINEX logger
PPP WizLite
Broadcom dubbed BCM47755 chipset
Xiamo Mi 8 (first dual frequency
smartphone) uses L1 and L5.
4Amir Allahvirdizadeh - Curtin University
1) Duty cycling: prevents continues phase measurements
5Amir Allahvirdizadeh - Curtin University
2) Antenna
not stable
the exact location is not known
Irregular gain pattern
poor multipath suppression
Slow convergence of PPP by smartphones
No ambiguity resolution
No accuracy
Amir Allahvirdizadeh - Curtin University
Duty cycling can be turned off in android 9
Using external antennas
7Amir Allahvirdizadeh - Curtin University
Review of the related projects
Rapid static mode
NRTK mode
PPP mode with GIM
Static mode using SSR data
Jamming detection
Apps with high accuracy GPS
Testing different antenna with smartphones
Flamingo Project
Dual frequency chipset
DF GNSS smartphones
8Amir Allahvirdizadeh - Curtin University
Rapid static mode
Carrier-phase-based differential mode
baselines ranging from 10 m to 8 km
GNSS data were collected by Geo++ RINEX Logger app
processed by the goGPS MATLAB software
The results show a quality similar to that of a standard single-
frequency low-cost receiver.
No Ambiguity Resolution
Smartphones are suitable to be used to perform rapid-static
surveys with decimeter-level accuracy.
9Amir Allahvirdizadeh - Curtin University
NRTK mode
Collecting data by Geo++ RINEX Logger and GNSS logger app
Located in a known point
The SPIN GNSS network used for NRTK positioning (VRS correction)
10 min of 1 Hz data processed by RTKLIB
The results show it is possible to perform NRTK positioning with
The precision is good but the accuracy is not.
The exact location of the internal antenna in not known
So fixing the ambiguities does not make sense.
10Amir Allahvirdizadeh - Curtin University
SF-PPP mode with GIM
1.5 h of GNSS data were collected by 3 devices
processed by RTKLIB
Global Ionospheric Map (GIM) files are used
The results show C/N values are low for cell phone. (38.7 dB-
Hz and is ~7.5 dB-Hz lower than the other devices)
It takes 15 min for converging to 2D error of < 1m (18 min for
Up component)
RMS for East, North and Up are: 25,28,51 cm respectively
11Amir Allahvirdizadeh - Curtin University
Static mode using SSR data
GNSS data were collected by GEO++ RINEX logger
use of SSR Post concept
SSR from Geo++® GNSMART
no chance to fix ambiguities due to different phase
5min convergence time to get 60 cm precision
absolute positioning in static mode using SSR data
from a sparse network (too slow for real time
12Amir Allahvirdizadeh - Curtin University
Jamming detection (e.g. STRIKE3)
13Amir Allahvirdizadeh - Curtin University
Apps with high accuracy GPS PPP-WizLite
14Amir Allahvirdizadeh - Curtin University
Testing different antenna with smartphones
Using Internal, External helical, External pinwheel
smartphone in metallic box to force phone to use these
C/N, pseudorange and position data confirm advantages
of external antennas
No smartphone hardware modification with use of
external antenna
15Amir Allahvirdizadeh - Curtin University
Flamingo Project
GOALS: deliver better than 50cm accuracy with
smartphones and IoT devices
employing multi-constellation, PPP and RTK mechanisms
Using Galileo High Accuracy Service
Develop “Rinex On” application
Will be available soon!
16Amir Allahvirdizadeh - Curtin University
Dual frequency chipset
17Amir Allahvirdizadeh - Curtin University
DF GNSS smartphones (Xiaomi mi 8)
Using “Rinex On” App to collect raw measurements
L1/L5 and E1/E5
Different positioning modes:
PPP mode (Post process and Real Time)
DGNSS mode
Uses NAVCAST GNSS PPP service for PPP in real time
Centimetre to decimeter-level accuracy achieved
18Amir Allahvirdizadeh - Curtin University
Future work could be…
Phase-centre identification of the smartphone GNSS antenna
Using external antenna and perform PPP-AR
Test single-base RTK positioning, considering a mass-market master station
Carrier-phase PVT
GNSS system monitor
Signal analysis (ionosphere, troposphere, SIS, multipath, radio noise)
Indoor positioning performance
Two-antenna phase array advantage for attitude determination and anti-jamming
IoT and LBS
Gesture and images or video correlated (Virtual or Augmented Reality).
19Amir Allahvirdizadeh - Curtin University
GNSS Raw Measurements Taskforce Workshop “GNSS Raw Measurements: From research to
commercial use”, GSA Headquarters, Prague, 30 May 2018.
Realini, E.; Caldera, S.; Pertusini, L.; Sampietro, D., Precise gnss positioning using smart devices.
Sensors 2017, 17 (10), 2434.
Dabove, P.; Di Pietra, V., Towards high accuracy GNSS real-time positioning with smartphones.
Advances in Space Research 2018, 63 (1), 94-102.
Banville, S.; Van Diggelen, F., Precise positioning using raw GPS measurements from Android
smartphones. GPS World 2016, 27 (11), 43-48.
Gill, M.; Bisnath, S.; Aggrey, J.; Seepersad, G. In Precise point positioning (PPP) using low-cost and
ultra-low-cost GNSS receivers, Proceedings of the ION GNSS, 2017; pp 226-236.
FLAMINGO – Discover rinexON 2018. (accessed October 10,
20Amir Allahvirdizadeh - Curtin University
Thanks for your attention
Amir Allahvirdizadeh
Curtin University
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Additional resources
There are a set of presentations about international services related to geodesy including IGS that are
available in [1], [2], [3] and [4]. Study [5] for the quality control of the GPS data. Different combinations
of noises in the time series of the IGS permanent station are also discussed in [6]. My thesis entitled
Evaluation of the GPS Observable Effects Located in the Earth Shadow on Permanent Station Position
Time Series” is available in [7] and the relevant paper is [8]. A useful presentation about extraction of
the atmospheric parameters from GPS products are available in [9].
[1] Allahvirdi-Zadeh, A., (2012). International GNSS Service (IGS): Structure, Data, and Products. In
Internal Student Seminars, Geomatics Engineering Department, University of Isfahan. DOI:
10.13140/RG.2.2.36805.09447/1 (
[2] Allahvirdi-Zadeh, A., (2012). International Earth rotation and Reference Systems Service (IERS):
Structure, Data, Products, Applications. In Internal Student Seminars, Geomatics Engineering
Department, University of Isfahan. DOI: 10.13140/RG.2.2.26817.40800/1
[3] Allahvirdi-Zadeh, A., (2012). International Doris Service (IDS): Data and Products. In Internal
Student Seminars, Geomatics Engineering Department, University of Isfahan. DOI:
10.13140/RG.2.2.27905.99681 (
[4] Allahvirdi-Zadeh, A., (2012). A deep look at the International Laser Ranging Service (ILRS). In
Internal Student Seminars, Geomatics Engineering Department, University of Isfahan. DOI:
10.13140/RG.2.2.17589.93923/1 (
[5] Allahvirdi-Zadeh, A., (2011). GPS Quality Control. In Internal Student Seminars, Geomatics
Engineering Department, University of Isfahan. DOI: 10.13140/RG.2.2.19189.01764
[6] Allahvirdi-Zadeh, A., (2011). Detect and Analysis of Noise with Different Combinations of Time
Series in IGS Permanent Stations. In Internal Student Seminars, Geomatics Engineering Department,
University of Isfahan. DOI: 10.13140/RG.2.2.21286.16965/2
[7] Allahvirdi-Zadeh, A., (2013). Evaluation of the GPS Observable Effects Located in the Earth Shadow
on Permanent Station Position Time Series. MSc Thesis, Geomatics Engineering Department,
University of Isfahan. DOI: 10.13140/RG.2.2.28151.32167
[8] Allahverdi-Zadeh, A., Asgari, J., & Amiri-Simkooei, A. R. (2016). Investigation of GPS draconitic year
effect on GPS time series of eliminated eclipsing GPS satellite data. Journal of Geodetic Science, 6(1).
DOI: 10.1515/jogs-2016-0007 (
[9] Allahvirdi-Zadeh, A., (2016). Extraction atmospheric parameters of GPS data. In Cloud seeding,
Physics department, Yazd University. DOI: 10.13140/RG.2.2.16882.15041
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
I introduced the international Doris Service in the internal seminars of the University of Isfahan. The Doris system is a french civil precise orbit determination and positioning system. It is based on the principle of the Doppler effect with a transmitting terrestrial beacons network and onboard instruments on the satellite's payload (antenna, radio receiver, and oscillator ultra-stable). Doris is one of three systems used for the precise determination of the Jason-1 satellite's orbit. Several of these techniques are sometimes merged on the same satellite: Jason-1 satellite includes three tracking systems, Doris, location by GPS, and laser telemetry. The Doris system perfectly corresponds to the specifications required for the ocean's topography observations and the amplitude of the observed phenomena: it is now enabled to measure the satellite position on its orbit close to 1 cm. It is interesting to compare this precision with the precision obtained at the beginning of the space age, where the satellite position was estimated close to 20 km then close to 20 meters in the '80s. Since 1998, the Diode navigator has added real-time measurement processing capability for satellite navigation. The Doris system was designed by CNES, the French space agency, in partnership with France's mapping and survey agency IGN and the space geodesy research institute GRGS. Since 2003, IDS is an international service that provides support, through Doris data and products. The successive missions since Spot 2 and Topex/Poseidon have truly demonstrated its performance.
Full-text available
I introduced the International Laser Ranging Service (ILRS), its data and products in the internal student's seminar at the University of Isfahan: Satellite Laser Ranging (SLR) and Lunar Laser Ranging (LLR) use short-pulse lasers and state-of-the-art optical receivers and timing electronics to measure the two-way time of flight (and hence distance) from ground stations to retroreflector arrays on Earth-orbiting satellites and the Moon. Scientific products derived using SLR and LLR data include precise geocentric positions and motions of ground stations, satellite orbits, components of Earth’s gravity field and their temporal variations, Earth Orientation Parameters (EOP), precise lunar ephemerides, and information about the internal structure of the Moon. Laser-ranging systems are already measuring the one-way distance to remote optical receivers in space and can perform very accurate time transfer between sites far apart. Laser-ranging activities are organized under the International Laser Ranging Service (ILRS) which provides global satellite and lunar laser ranging data and their derived data products to support research in geodesy, geophysics, Lunar science, and fundamental constants. This includes data products that are fundamental to the International Terrestrial Reference Frame (ITRF), which is established and maintained by the International Earth Rotation and Reference Systems Service (IERS). The ILRS develops the necessary global standards/specifications for laser ranging activities and encourages international adherence to its conventions.
Full-text available
I introduced the International Earth Rotation and Reference Systems Service (IERS) at the University of Isfahan: The IERS was established in 1987 by the International Astronomical Union and the International Union of Geodesy and Geophysics. According to the Terms of Reference, the IERS accomplishes its mission through the following components: Technique Centres, Product Centres, Combination Centres, Analysis Coordinator, Central Bureau, Directing Board. The IERS provides data on Earth orientation, on the International Celestial Reference System/Frame, on the International Terrestrial Reference System/Frame, and on geophysical fluids. It maintains also Conventions containing models, constants, and standards.
Full-text available
I introduced the International GNSS Service in the internal students' seminar at the University of Isfahan: The International GNSS Service (IGS) has ensured open access, high-quality GNSS data products since 1994. These products enable access to the definitive global reference frame for scientific, educational, and commercial applications – a tremendous benefit to the public, and a key support element for scientific advancements. The IGS at a Glance A voluntary federation of over 200 self-funding agencies, universities, and research institutions in more than 100 countries; working together to provide the highest precision GPS satellite orbits in the world. Providing free and open access to the highest precision products available for scientific advancement and public benefit. These products support a wide variety of applications that touch millions of users in virtually all segments of the global economy Producing products that support the realization of the International Terrestrial Reference Frame while providing access to tracking data from over 400 worldwide reference stations Working for the continuous development of new applications and products through Working Groups and Pilot Projects Supporting geodetic research and scholarly publications Functioning as a component of the Global Geodetic Observing System (GGOS) and member of the World Data System (WDS).
Full-text available
In this project, I will demonstrate the process of analyzing GPS time-series data. I have used 10 years of continuous GPS measurements of four stations (ALGO, GRAZ, KOSG, and ONSA) and three different combinations of the noise component of GPS coordinate time-series, i.e., White noise, Flicker noise, and random walk noise. I use Least Squares Variance Component Estimation (LS-VCE) instead of Maximum Likelihood Estimation (MLE) because of its advantages.
Full-text available
"Extraction atmospheric parameters of GPS data" is the title of a workshop I held for the cloud seeding staff and graduate students of the Physics department of Yazd University. It was about how to extract atmospheric parameters from GPS data and services and analyze them to calculate the Predicted Water Vapor (PWV).
Full-text available
Few decimetre to metre level accuracy is possible using the cellphone grade GNSS hardware. Current low-cost and ultra-low-cost (cellphone) GNSS receivers have no dual-frequency observables to form linear combination, in-order to account for the ionospheric delay. Global Ionospheric Maps (GIM) are used to mitigate the ionospheric error. Signal-to-noise ratio (í µí° ¶ í µí± 0 ⁄) of cellphone antenna is on average 7.5 dB-Hz low compared to the geodetic-grade antenna which depicts that the quality of the raw observations from cellphone GNSS hardware is of low quality compared to the raw observables from geodetic-grade and u-blox hardware. Raw measurement analysis (í µí° ¶ í µí± 0 ⁄) and post-fit residuals show that signal from cellphones are more prone to multipath compared to signals from geodetic-grade and u-blox receivers. The primary reason for multipath is circular polarized antenna in the cellphones. Irregular gain pattern and poor multipath suppression of cellphone antenna is also the primary reason for the slow convergence of Precise Point Positioning (PPP) solution compared to PPP solution with geodetic-grade hardware. Positioning results from cellphone processing are inferior to the geodetic-grade hardware. However, horizontal and vertical RMS of 37 cm and 51 cm, respectively, is achieved using cellphone.
Full-text available
Spectral analysis of time series is an important issue in Geodesy. The main purposes of this analysis are detecting periodic behavior and the sources of these behaviors. Periodic signals and their harmonics are causes of reduced accuracy in time series analysis. Therefore these signals should be detected and removed from the results. One of these Periodic behaviors in the time series of IGS products is GPS draconitic year. GPS draconitic year is the time taken for the Sun (as seen from the Earth) to complete one revolution with respect to the GPS orbital nodes. It takes 351.2 days. Harmonics of the GPS draconitic period are observed at almost all IGS products such as position time series for IGS permanent stations. From 2007 until today, many studies are done on IGS products to explore the factors of this period and its harmonics such as (Ray 2007, Tregoning 2010, and Griffiths 2012). Orbital errors and local multipath are known as two sources of these signals. In this thesis, the effect of crossing GPS satellites from the shadow of the earth on the harmonic signals matched with the GPS draconitic period is introduced. GPS satellites at different blocks show different behaviors when crossing the shadow of the earth. By analyzing these behaviors a decision has been made to write a toolbox in the programming environment of MATLAB to remove the observations of eclipsed satellites. Spectral analysis of the data shows that spectral values on most harmonics become smaller after removing eclipse satellites.
Full-text available
GPS draconitic signal (351.6 ± 0.2 days) and its higher harmonics are observed at almost all IGS products such as position time series of IGS permanent stations. Orbital error and multipath are known as two possible sources of these signals. The effect of Earth shadow crossing of GPS satellites is another suspect for this signal. Up to now, there is no serious attempt to investigate this dependence. A MATLAB toolbox is developed and used to determine the satellites located in the earth's shadow. RINEX observation files and precise ephemeris are imported to the toolbox and a cylindrical model is used to detect the shadow regions. Data of these satellites were removed from the RINEX observation files of three IGS permanent stations (GRAZ, ONSA, and WSRT) and new RINEX observation files were created. The time span of these data is about 11 years. The new and original files were then processed using the precise point positioning (PPP) method to determine position time series, for further analysis. Both the original and new time series were analyzed using the least-squares harmonic estimation (LS-HE) in the following steps. The 1st step is the validation of the draconitic harmonics signature in the original position time series of the three stations. The 2nd step does the same for the new time series. It confirms that the power spectrum at the draconitic signals decreases to some extent for the new time series. The difference between the original and new time series (difference between all three position quantities (X, Y, and Z)) is then analyzed in the 3rd step. Signature of the draconitic harmonics is also observed to the differences. The results represent that all eight harmonics of the GPS draconitic period do exist at the residuals and mainly they decrease. All of the three stations were then processed together using the multivariate LS-HE method. At the 4th step, the difference of the spectral values between the original time series and new times series were analyzed. Decreasing the spectral values at most harmonics (e.g. 1st, 2nd, 4th, 6th, 7th, and 8th) represents the effect of removing satellite observations at the shadow of the earth on draconitic harmonics. At least, five harmonics among seven shows the amelioration of results (draconitic error reduction) after removing the earth shadowed data from RINEX raw data. The results show that the draconitic year’s component of data is in part due to eclipsing satellites.
Full-text available
During its “I/O 2016” conference held in May 2016, Google announced that raw GNSS measurements from smartphones and tablets running the Android N (“Nougat” = version 7) operating system would be made available to developers. The implications of this initiative are significant for the community since it allows us to move away from the black-box concept of the GNSS receiver providing meter-level accuracies and opens up the possibilities of using pseudorange, Doppler and carrier-phase measurements to derive more accurate positions. Even if the low-cost GNSS antennas and chips contained in smartphones will never outperform high-end geodetic instruments, it is an interesting research avenue to investigate how far these devices can take us. This opportunity could in turn spark the emergence of new applications that would not have been envisioned before.