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Received February 25, 2021, accepted March 6, 2021, date of publication March 29, 2021, date of current version April 13, 2021.
Digital Object Identifier 10.1109/ACCESS.2021.3069315
Positioning in the Arctic Region: State-of-the-Art
and Future Perspectives
ANASTASIA YASTREBOVA 1, MARKO HÖYHTYÄ 1, (Senior Member, IEEE),
SANDRINE BOUMARD1, ELENA SIMONA LOHAN 2, (Senior Member, IEEE),
AND ALEKSANDR OMETOV 2, (Member, IEEE)
1VTT Technical Research Centre of Finland Ltd., 90570 Oulu, Finland
2Electrical Engineering, Tampere University, 33720 Tampere, Finland
Corresponding author: Anastasia Yastrebova (anastasia.yastrebova@vtt.fi)
This work was supported by the VTT New Space Program under Project FAST4NET. The work of Elena Simona Lohan was supported by
the Academy of Finland under Project ULTRA.
ABSTRACT The positioning systems’ high accuracy and reliability are crucial enablers for various future
applications, including autonomous shipping worldwide. It is especially challenging for the Arctic region
due to the lower number of visible satellites, severe ionospheric disturbances, scintillation effects, and
higher delays than in the non-Arctic and non-Antarctic regions. In regions up North, conventional satellite
positioning systems are generally proposed to be utilized, together with other situational awareness systems,
to achieve the necessary level of accuracy. This paper provides a detailed review of the current state-of-
the-art, satellite-based positioning systems’ availability and performance and reports high-level positioning
requirements for the oncoming applications. In particular, the comparative study between three Global
Navigation Satellite System (GNSS) constellations is executed to determine whether they are suitable for
autonomous vessel navigation in the Arctics’ complex environment as the two most significant drivers for
a reevaluation of the related satellite constellations. This work analyzes the ongoing research executed
in different (inter-) national projects focused on Galileo, Global Positioning System (GPS), and GLObal
NAvigation Satellite System (GLONASS). Based on the literature review and the simulation campaign,
we conclude that all the convectional constellations achieve an accuracy of fewer than three meters in the
analyzed Arctic scenarios. It is postulated that other complementary positioning methods should be utilized
to improve accuracy beyond this limit. Finally, the study emphasizes existing challenges in the Arctic region
regarding the localization and telecommunication capabilities and provides future research directions.
INDEX TERMS Marine navigation, Arctic, global positioning system, aerospace simulation, unmanned
autonomous vehicles.
I. INTRODUCTION
The Arctic region is one of the leading developing prospects
for various industries, including offshore extraction of
resources and minerals, observational ecologies, such as
Bentho-Pelagic monitoring [1], as well as one of the fore-
most maritime trading paths between the Atlantic and Pacific
oceans [2]. It has been long observed that the shipping opera-
tions and the activities on the exploration of natural resources
could be affected by poor navigational services and com-
plex communication situations [3]. Furthermore, navigation
in the Arctic is more demanding due to challenging weather
conditions, ionospheric effects, complex properties of the
The associate editor coordinating the review of this manuscript and
approving it for publication was Hayder Al-Hraishawi .
ice surface, and mobility [4]. Today, the primary option for
communications and navigation in the deep waters of the
Arctic region is the satellite connectivity [5]. Additionally,
the onshore infrastructure also provides timely notifications
and precise positioning information from and to the vessels
in order to minimize the possible damage caused by the
potentially dangerous and unpredictable environment when
available [6].
Wireless positioning is significant for the oncoming era of
the Arctic region operation and, especially, autonomous ves-
sel operation integrated with various robotic systems [7], [8].
It is vital to understand the threshold for an accurate posi-
tioning in the open sea and the harbor for safe maritime
operations of crew-less vessels [9]. The positioning accu-
racy requirements may differ tremendously depending on
53964 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 9, 2021
A. Yastrebova et al.: Positioning in Arctic Region: State-of-the-Art and Future Perspectives
TABLE 1. Summary of literature review and author contributions.
the application’s environment: whether the system provides
primary navigation in the open sea or a precise positioning
service for heavy traffic environmental conditions, such as a
marine port. At sea, the accurate positioning ensures that the
vessel reaches the destination on time most safely and cost-
effectively. The need for accurate positioning in the harbor
is critical due to short distances, increased vessel traffic, and
possible obstacles that make maneuvering more difficult in
comparison to deep-water missions.
The Arctic region, defined as the region above the Arctic
circle (or 66.56 degrees latitude North), is known for being a
challenging area, not only due to severe weather but also due
to wireless telecommunication and positioning limitations.
Many research groups have delved into the Arctics research
in this field [5], [56]–[58]. One of the challenges causing
a reduction in the Arctic satellite positioning performance
is related to ionospheric and tropospheric disturbances that
cause random delays and scintillation of the satellite sig-
nals [5]. These effects are even greater when the satellite is
closer to the horizon [59], [60]. The survey [4] mainly indi-
cates that the GNSS performance in the Arctic is sub-optimal.
The GNSS satellite constellation geometry, typically mea-
sured through the Geometric Dilution of Precision (GDOP)
metric, causes another positioning-related challenge. The
associated problem may be related to the constellation design
of many medium Earth orbiting (MEO) positioning satellites
and the affected time shifts. As discussed in [61], the satellite
visibility from the low-elevation angles may be obstructed by
location-specific conditions, and signals from high-elevation
angles are unavailable due to time- and location-specific con-
ditions. Moreover, the received signal suffers from possible
blockages due to icebergs, hills, other vessels, etc., causing
multipath. The operational scenarios of the positioning in the
Arctics are, indeed, vast, see Fig. 1.
Several techniques aim to improve the positioning perfor-
mance, such as differential positioning, satellite-based aug-
mented systems, and satellite-based automated identification
FIGURE 1. High-level autonomous vessel positioning architecture.
data exchange systems. Other techniques may involve Earth
Observation (EO) systems to map the region with potential
challenges, such as formations of ice or icebergs (as well
as their mobility) to provide enhanced information to the
vessels. Vessels may use the EO data with a geotag to iden-
tify those regions in advance and possibly avoid them. This
technique will not achieve a sub-meter-level positioning, but
it might support other techniques to improve positioning
performance. A combination of space and terrestrial sensing
techniques can provide more in-depth and more redundant
information on the environment by validating both systems’
information. The intelligent combination of these techniques
may be vital for enabling reliable positioning in the Polar
regions.
Table 1provides a summary of related works and indi-
cates contributions of the current work. During the literature
review, it was found that the topic of positioning regarding
autonomous systems is lacking. Thus, this paper contributes
to the overall picture by studying the positioning require-
ments and performance, focusing on autonomous systems,
such as autonomous vehicles and vessels operation.
The rest of the paper is organized as follows. Section II
describes the positioning requirements for autonomous
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A. Yastrebova et al.: Positioning in Arctic Region: State-of-the-Art and Future Perspectives
TABLE 2. Positioning requirements depending on the application and
service availability based on [62].
vessels and the current state of standardization. Section III
discusses ongoing projects aiming to advance the posi-
tional accuracy, specifically in the Polar regions, with the
classification into space, terrestrial, and research activities.
In Section IV, the architecture of autonomous vessels’ posi-
tioning is described, including step-by-step operations and
the simulation environment, focusing on GNSS constellation
analysis for the Arctic region. Next, in Section V, we provide
the results of our simulation system. Further, Section VI sheds
some light on the future perspectives of the related posi-
tioning challenges and potential solutions. The last section
concludes the discussion.
II. TECHNICAL REQUIREMENTS, STANDARDIZATION,
AND REGULATIONS
A. TECHNICAL REQUIREMENTS
Positioning is an essential feature to sail safely and track
goods anywhere, which is also very important in icy Arctic
conditions. Accurate and reliable positioning will be espe-
cially critical in future autonomous systems that will operate
without the onboard crew’s support.
Positioning requirements for autonomous vessels are not
standardized yet (ongoing work is described in 3GPP [10],
and requirements for maritime use cases related to the
goods tracking are described in [11]). Netherlands Regulatory
Framework (NeRF) describes future GNSS requirements,
a summary of the requirements provided in Table 2. Accord-
ing to the revised maritime policy [62], the general require-
ment for the positioning is 10 m of horizontal accuracy.
However, for specific applications, such as ice-breaking and
hydrography, the required accuracy is 1-2 meters with service
availability of 99.8% per 30 days. The policy also specifies
the cases’ positioning requirements, such as automatic dock-
ing – accuracy must be 0.1 meter. The requirements might be
tightened for the speed of the vessel above 30 knots.
B. THE INTERNATIONAL MARITIME ORGANIZATION
REGULATIONS
Broadly, the International Maritime Organization (IMO) has
published The International Regulations for Preventing Col-
lisions at Sea (COLREGS) [12] in 1972, where the require-
ments and rules for the operations on a vessel are described.
These requirements refer to the vessel equipment, its use,
and the rules for the onboard passengers. According to these
regulations, ‘‘every vessel shall at all times maintain a proper
look-out by sight and hearing as well as by all available means
appropriate in the prevailing circumstances and conditions to
make a full appraisal of the situation, and the risk of colli-
sion’’ (COLREGS rule 5) [12]. Also, ‘‘vessels are required to
make proper use of radar equipment to obtain early warning
of the risk of collision, to use radar plotting or equivalent
systematic observation of detected objects, and are warned
that assumptions shall not be made based on scanty informa-
tion’’ (COLREGS rule 7b,c) [63].
The regulatory framework is limited to human vision
and hearing, and the vessel equipment such as radar, Auto-
matic Radar Plotting Aid (ARPA), Automated Identification
System (AIS), Electronic Chart Display Information Sys-
tem (ECDIS), and GNSS. For autonomous vessels, the use
of only these technologies cannot ensure the safety of nav-
igation. The IMO is currently conducting a regulatory cam-
paign to provide a set of recommendations for the safe and
secure operation of partly or wholly autonomous vessels and
their interactions with other traffic participants. The research
and development are currently limited to within national
waters [64].
III. TECHNOLOGY REVIEW
Currently, the satellite capabilities in northern regions do
not entirely fulfill the autonomous vehicle operation require-
ments in communications and positioning. These limita-
tions include ionosphere signal disruption and attenuation,
troposphere effects, etc. Due to these challenges, neither
autonomous vessels nor any other unmanned surface vehicles
can exploit their potential in the Arctic regions. To address
these challenges, both industry and academia perform a sig-
nificant number of trials and research activities. The ongoing
research is mainly concentrated in several areas: the terrestrial
infrastructure, the space systems, and possible techniques to
mitigate the satellite reception’s scintillation [21], [24], [28],
[52]–[55], [65].
As of today, the Arctic region space infrastructure provides
the following abilities [66]:
•Navigation satellites and space-based augmentation sys-
tems;
•Remote sensing and Earth observation techniques;
•Satellite-based Automated Identification (SAT-AIS)
Data Exchange Systems for maritime communications;
•Satellite navigation for tracking and different types of
vehicles (manned and unmanned).
In the current section, we will review technologies, start-
ing from the GNSS characteristics and different positioning
techniques, followed by the combination of different satellite
and terrestrial applications to improve positioning. We will
also review ongoing strategic work and provide highlights
and objectives of each project.
A. GLOBAL NAVIGATION SATELLITE SYSTEMS AND
AUGMENTATION SYSTEMS
1) SYSTEMS AND THEIR CHARACTERISTICS
The term GNSS covers all global positioning satel-
lite systems that continuously transmit signals, which
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TABLE 3. GNSS constellations’ main parameters.
enable users to determine their position on the Earth:
GPS (initially developed for military purposes); GLONASS,
Galileo, and Beidou.
Every satellite positioning system is different concerning
orbital altitude, the satellites’ positioning in orbit, and the
number of satellites. The main parameters of the examined
GNSSs are given in Table 3[14], [67]–[72].
The Russian GLONASS has the highest orbital inclination,
compared with other systems, potentially implying better
performance in the Arctic region. GPS satellite orbital planes
incline 55o, resulting in potential performance challenges at
high latitudes. This tendency is also present for the other
two systems – the European Galileo system and the Chinese
Beidou. The latter provides its best coverage in the Asia-
Pacific region [67].
Standard Positioning Service (SPS) is a positioning
and timing service provided by all satellites in the con-
stellation [13]. Specifically, SPS is the characteristic of
GPS. However, similar technologies are implemented for
GLONASS (Standard Accuracy Signal service) [14], and
Galileo (Open Service (OP)) [15]. For the positioning service
to work accurately, the receiver shall have an unobstructed
view of at least four satellites to calculate three position
coordinates and the clock deviation. The data provided from
the satellites allows the user to calculate the approximate
distance from the satellite to the receiver, based on the time
the signal has traveled [73]–[75]. The GNSS performance in
polar regions is related to the satellite constellations’ geome-
try; the inclination data can be found in Table 3.
2) ASSISTANCE SYSTEMS TO IMPROVE ACCURACY
Besides the geometry limitations, high latitudes introduce
significant oscillation and delay of the signals due to the
ionosphere layer. Several techniques aim to improve the
positioning performance. The most common position ref-
erence methods involve Global Positioning System (GPS)
satellites and the differential GPS (DGPS) position refer-
ence method, which combines GPS positioning together
with the fixed ground-based reference station. A DGPS
can provide accuracy, in case of best implementation, of
1 meter for users in the range of a few tens of kilo-
meters from the reference station [19]. However, the sig-
nal’s degradation is mostly caused by the atmospheric
disturbances or blockage of line-of-sight (LoS) [20]. For
comparison, for a stand-alone receiver that uses only the
satellites’ signals, the accuracy performance levels vary from
2 to 10 meters [71].
Another technique to improve positioning is the real-time
kinematic (RTK) positioning that implies the use of a ref-
erence radio signal from a fixed base station [16]. RTK is
referred to as a differential GNSS, and this method suffers
from similar issues as DGPS. This method provides an accu-
racy of 0.01–0.03 meters. However, this method’s applicabil-
ity area is limited since the reference station should be close
to the receiver to provide support [17], [18].
3) SPACE-BASED AUGMENTATION SYSTEMS
Another method to improve the GNSS reception in high
latitudes includes the use of the space-based augmentation
systems (SBAS) [76].
SBAS is usually developed for specific purposes. Exam-
ples of these systems are the North American Wide Area
Augmentation System (WAAS) with intended coverage over
the United States, Canada, and Mexico [77] and the Euro-
pean Geostationary Navigation Overlay Service (EGNOS),
providing service in Europe [78]; both are developed for the
aviation purposes.
The EGNOS Safety of Life (SoL) service provides
integrity information that is a measure of the trust that can
be placed in the correctness of the information provided by
a navigation system. The disadvantage is that both services
rely on GEO satellites, which are not visible above 72 degrees
North. However, the services have been successfully used for
the GNSS-based landing operation below that latitude [79].
To resolve that problem, a new service, Advanced Receiver
Autonomous Integrity Monitoring (ARAIM), is being under
joint development by the EU and US and will start ini-
tial operation in 2025. The service will provide improved
integrity, in particular for aviation and maritime sectors [79].
Currently, the EGNOS system supplements the GPS, but the
system will also supplement the European Galileo in the
future.
Meanwhile, the GALILEO Open Service and Search and
Rescue (SaR) service are available in the Artic [79]. The
Galileo Open Service supports positioning, navigation, and
timing synchronization. The SAR Service improves the local-
ization of the distress signals and is used for SAR opera-
tions and covers the Arctic region up to 85 degrees North
latitude. This service helps to reduce the uncertainty down
to less than 5 kilometers. The service’s major upgrade is
the Galileo Return Link option that became operational on
January 21, 2020 [80]. The return link broadcasts a con-
firmation to the user that the distress message has been
received.
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4) GROUND-BASED AUGMENTATION SYSTEMS (GBAS)
GBAS is a system that provides a local augmentation of the
primary GNSS constellations. This method offers integrity
assurance and increased portioning accuracy with position
errors below 1 meter. GBAS was developed for civil avia-
tion in order to resolve real-time integrity monitoring issues.
Pseudolites can be considered as an example of GBAS. Pseu-
dolites are transceivers that are used to create a local ground-
based alternative to GPS. They are used to provide extended
coverage during poor satellite availability and improve GPS
integrity and reliability. Pseudolites are independent of GPS
and are used to augment the GPS by improving dilution of
precision [81], [82].
5) MULTI-GNSS POSITIONING
Many works have considered the use of multiple GNSS
constellations to improve integrity and coverage [83], [84].
Due to the GNSS constellations’ design, the positioning per-
formance is better in mid and low latitudes. In this case,
especially in the polar regions, multi-GNSS advantages may
include increasing satellites’ availability and positional accu-
racy and reliability. However, the combined usage requires
taking into account the variable interference and time offset
between the individual system times, thus increasing the
complexity of the system [85]. One of the major international
activities related to multi-GNSS positioning is the Interna-
tional GNSS Service (IGS) - an international organization
that involves over 200 participants, with the primary goal
to support research related to the highly accurate combined
utilization of GNSS. IGS has organized the multi-GNSS
Experiment (MGEX) pilot project to collate and analyze all
available GNSS signals. A network of multi-GNSS stations
was established and integrated with the existing network of
reference stations, including the polar regions [86], [87].
B. CURRENT TRACKING SYSTEMS
Potentially, satellite technologies may provide tracking capa-
bilities at high latitudes to overcome terrestrial coverage limi-
tations. The current section provides an overview of such used
and future systems.
1) SATELLITE-BASED AUTOMATED IDENTIFICATION DATA
EXCHANGE SYSTEMS (SAT-AIS) FOR MARITIME
COMMUNICATIONS
The Automatic Identification System (AIS) is an automatic
tracking system that is executed by transceivers on the ves-
sels or by land-based systems and is used by vessel traffic ser-
vices (VTS) [22]. The vessels of 300 gross tonnage or more
sailing in the international waters and all passenger ships,
regardless of the size, are required by IMO to have the AIS
equipment operational.
The AIS signals have a horizontal range of about
40 nautical miles (74 km). That means that AIS infor-
mation can only be available near the coastal areas or in
a ship-to-ship line of sight. AIS equipment integrates the
Very High-Frequency (VHF) transceiver (frequencies
161.975 MHz and 162.025 MHz, using 25 kHz bandwidth)
and a satellite positioning system with other electronic nav-
igation sensors. The satellites are used to detect AIS sig-
natures, such as unique identification, position, course, and
speed beyond the coastal area. This information is used to
supplement marine radar. It should be noted that the degraded
navigation solution will degrade the AIS use as well. The
work [88] demonstrated the performance of AIS when the
GPS signal was jammed. With total GPS denial, the AIS was
unable to calculate the range to nearby vessels.
In order to provide the integrity of the navigational sys-
tem for AIS use, ESA is cooperating with the European
Maritime Safety Agency (EMSA) in order to deliver a
European-based, satellite-based AIS (SAT-AIS) system that
will increase the coverage and effectiveness of vessel traffic
services [22], [23].
SAT-AIS is being developed through the Advanced
Research in Telecommunications Systems (ARTES) program
elements that include
•ARTES 5 – technology pre-development activities, such
as antenna miniaturization, receiver developments, and
a performance testbed;
•ARTES 20 – implementation and validation of a Data
Processing Centre in cooperation with the European
Maritime Safety Agency;
•ARTES 21 phase 1 – initial steps of the system design
and implementation;
•ARTES 21 phase 2 – covers the detailed design and
implementation of the SAT-AIS microsatellites and pay-
loads and the development of innovative SAT-AIS appli-
cations and services.
2) MICROSATELLITES
Following the system definition and trade-off analysis car-
ried out within SAT-AIS work, a new microsatellite ESAIL
project was established due to the Public-Private-Partnership
of LuxSpace with ESA in the ARTES program [24], [25].
Within the current project, a constellation of microsatellites
has been designed to be the most cost-effective solution
for providing SAT-AIS services and maintaining its viabil-
ity [89]. The developed ESAIL microsatellites provide world-
wide tracking capabilities for the vessels. ESAIL satellites
will be launched into a Sun-synchronous orbit at an altitude
of around 500 kilometers.
Generally, small satellite constellations nowadays are
becoming more popular due to faster production and
relatively cheaper launch into the orbits [90]. Usually,
those satellites are placed at the LEO or Sun-synchronous
orbits at a very low altitude. Several companies are
developing and launching the constellations of small
satellites for a variety of missions. Some of them
include tracking services for maritime (ESAIL), avia-
tion (Aistech [26]), and land vehicle (Astrocast [27])
domains.
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C. REMOTE SENSING AND EARTH OBSERVATION
TECHNIQUES TO IMPROVE POSITIONING
A combination of space and terrestrial sensing techniques can
provide more in-depth and more redundant information on
the environment by validating both systems’ information. The
current section describes examples of these techniques.
1) SATELLITE-BASED EARTH OBSERVATION (EO)
TECHNIQUES
Earth observation and remote sensing techniques can provide
strong support for safe navigation in the Arctic. While space-
borne AIS receivers are used to track AIS-enabled vessels,
Earth observation satellites can detect other non-AIS-enabled
vessels; for example, the vessels are less than 300 gross
tonnage and are not required to have AIS equipment on board.
The information about the position of such non-AIS-enabled
vessels can be distributed to other neighboring vessels to
avoid the collision [91].
Another usage of EO satellites is the mapping of the ice
conditions in the sea [79]. One of the challenges the vessels
face in the Arctic regions is the lack of accurate maps, espe-
cially depth maps. An inaccurate depth map could lead to
vessel grounding.
One of the Earth observation programs is the Copernicus
program, which includes six dedicated satellites for informa-
tion gathering and six operational thematic services for infor-
mation distribution in the Arctic [28], [79]. The Copernicus
Marine Environment Monitoring Service (CMEMS) provides
information about the marine environment, such as water
conditions, sea ice coverage, iceberg concentration, and so
on [29].
The Copernicus Atmosphere Monitoring Service (CAMS)
provides information on atmospheric composition and
solar radiation [30]. The Copernicus Climate Change Ser-
vice (C3S) delivers maps of sea ice in both the Arctic and
Antarctic areas [32]. The Copernicus Land Monitoring Ser-
vice (CLMS) monitors the snow cover, lake ice, inland water
volume, and its quality [31].
Artificial Intelligence (AI) for space technologies is cur-
rently extensively studied by many researchers. The Danish
Meteorological Institute (DMI), the Technical University of
Denmark, and Harnvig Arctic & Maritime have initiated the
Automated Sea Ice Products (ASIP) project, where the aim
is to develop an automatic sea-ice service that can provide
timely ice-mapping information and thus increase efficiency
and safety of marine operations [33]. The project aims to
merge the satellite imagery with other sensor data, such as
passive microwave data, to resolve uncertainty in synthetic-
aperture radar (SAR) imagery using Convolutional Neural
Networks (CNN).
2) TERRESTRIAL TECHNIQUES
The terrestrial sensors may compliment EO satellites by
providing information used to validate the satellite images
and increase the accuracy of positioning by using additional
reference frames to improve the satellite imagery data. In this
review, we highlight acoustic and laser ranging techniques as
mostly studied in modern literature.
a: ACOUSTIC TECHNIQUES
An example of such implementation can be named the Inte-
grated Arctic Observing System (INTAROS) project [34].
INTAROS is an ongoing research and innovation project
under the H2020-BG-09 call, which began in 2016 and will
run until 2021. The project’s overall objective is to develop
a sustainable integrated Arctic Observation System (iAOS)
by complementing the existing systems in the Arctic. The
iAOS will contain a multi-purpose acoustic network designed
for positioning, tomography, and communications. These net-
works have been used locally in the Arctic for underwa-
ter acoustic thermometry and for positioning for floats and
gliders.
In the future, the Coordinated Arctic Acoustic Thermome-
try Experiment (CAATEX) is planned within the INTAROS
project [36]. The problem that is being observed within
the CAATEX is secure data delivery. The current solu-
tion lies in using submarine cables that are the dedicated
cabled observatories. Several large-scale cabled observato-
ries are existing coastal areas in the world oceans, but none
on the Arctic Ocean. The considered solution consists of
integrating sensors into future undersea telecommunications
cables, which would create Science Monitoring And Reliable
Telecommunications (SMART) subsea cable systems. The
SMART sensor will take measurements of underwater pres-
sure and temperature [35]. The INTAROS project is currently
developing a Roadmap for the integrated Arctic Observing
System [36].
b: LASER-RANGING TECHNIQUES
In 2017, the National Aeronautics and Space Administra-
tion (NASA), together with the Norwegian Mapping Author-
ity, has started the development of a laser-ranging station
within NASA’s Space Geodesy Project (SGP) [37]. The laser-
Ranging station will be placed around 1,050 kilometers away
from the North Pole in the scientific base of Ny −lesund,
Svalbard. Continued development of the station will con-
tribute to the satellites’ high-precision positioning and oper-
ations on ice sheet tracking and improving transportation
in the current region. The current station will complement
the global network of space geodetic stations to provide
information about the Earth by monitoring the position over
time, the planet’s size, and shape. The system uses the light
measurements (the time it takes for the light to travel back
to its point of origin) due to which the satellite location can
be established with respect to the ground station with an
accuracy of around 1 millimetre [38].
The purpose of the SGP is to develop sustainable NASA’s
legacy Space Geodesy Networks by constructing, deploying,
and maintaining the next-generation Space Geodesy stations
and contributing to the Global Geodetic Observing System.
One of the main objectives of the SGP is to develop a
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Terrestrial Reference Frame that has an accuracy of 1 mm
with stability at 0.1 mm/year [37], [92].
D. HYBRID SATELLITE-TERRESTRIAL SYSTEMS
Hybrid satellite-terrestrial techniques to improve position-
ing include utilizing different systems, such as land-
based external reference systems, cameras, radars, etc.
These pose a challenge for an appropriate sensor fusion
algorithm application. The current section discusses how
data from multiple systems can be combined to improve
positioning.
1) CONNECTIVITY DEVELOPMENT AND 3-DIMENTIONAL
NETWORKS
In order to improve the positioning accuracy, hybrid posi-
tioning techniques can be applied. Extensive work has been
already done on the existing solutions to add positioning
and collision avoidance redundancy in the autonomous vessel
operation [8], [39]–[44]. The hybrid positioning techniques
may include land-based external reference systems for aided
navigational reliability when operating in the proximity of
the shore. Land-based cameras and radars can be used to
navigate the vessel along the shore safely. As GNSS signals
may not always be available and sufficient, the cellular-
based positioning techniques can also be useful when
available [45].
Several methods are used to determine the position of
an autonomous vehicle or a vessel. Those methods include
various communication technologies, such as utilized in
urban/rural areas – Wi-Fi, LTE, etc., as well as cameras,
radars, and physical landmarks [39]. The location can be
determined through the sensor fusion of several technologies.
In this case, the need for communications increases as vehi-
cles can send information about their location through the
mobile communications network infrastructure.
For air navigation in the Arctic region, a satellite naviga-
tion system or ground-based radio navigation equipment is
used as the primary system. Standard ground-based naviga-
tion equipment operates using Distance Measuring Equip-
ment (DME) and the Instrument Landing System (ILS).
The ground-based systems are used for rail traffic as well.
Satellite-based positioning has replaced the VHF Omni-
directional Range (VOR) and is supported by radar control
for location determination. The satellite navigation will also
complement the radars and radio systems for vessels and the
visual safety systems [93].
The maritime solutions to support activities in the Arctic
are also being investigated by the Technical Research Centre
of Finland VTT Ltd [94]. The current study is partly car-
ried out in the ongoing internal project FAST4NET (Fea-
sibility Studies and Tools for Multilayered Non-Terrestrial
and Terrestrial 3GPP Networks), where one of the main
study items is the heterogeneous architecture for different
autonomous system-use cases for in-land and maritime envi-
ronment besides the positioning.
2) COMBINATION OF SENSOR DATA TO IMPROVE
POSITIONING
The autonomous vessels and vehicles are likely to use many
supporting systems for positioning estimation, and another
intuitive step to improve positioning accuracy is to use sen-
sor fusion for navigation. Both autonomous systems get
the positioning data not only from GNSS satellites but
also from the gyro-compass, internal motion units (IMU),
and additional sensors, such as Sound Navigational Rang-
ing (SONAR), laser-based position reference systems, such
as Light Detection and Ranging (LiDAR), as well as the
radar-based systems [8], [46], [47]. The use of many tech-
nologies is essential, as no single sensor technology can
provide satisfactory performance considering different envi-
ronmental conditions. Therefore, to guarantee that the ves-
sel’s or vehicle’s surroundings are accurate, the data from
multiple sensors shall be combined and analyzed. A robust
sensor fusion algorithm is needed to aggregate data from
different sensors for continuous positioning and situational
awareness [48].
E. ONGOING STRATEGIC WORK
There are many monitoring activities and improving position-
ing and communication infrastructure in the Arctic described
in the current section. The summary of the projects is pre-
sented in Table 4.
1) SAON
Sustaining Arctic Observing Networks (SAON) is a joint
activity of the International Arctic Science
Committee (IASC) and the Arctic Council, which started
in 2007, whose purpose is to support the development of
multinational cooperation for sustained and coordinated pan-
Arctic observation and data sharing systems [65]. SAON’s
main vision is to offer users free, open, and high-quality
data to provide global societal benefits. Aiming to achieve
that, in 2018, SAON issued a strategy [49] and implemen-
tation [98] plan for the next ten years. The strategy aims to
address current and future Arctic observing needs to promote
free and ethically open access to all Arctic observational data
and ensure Arctic observing’s sustainability.
2) EU-POLARNET
EU-PolarNet is the world’s largest consortium of expertise
and infrastructure for polar research, consisting of seventeen
countries [50]. EU-PolarNet will develop a strategic frame-
work and mechanism to optimize the current Arctic infras-
tructure. The consortium aims to develop an integrated EU
Polar research program by identifying short- and long-term
scientific needs and optimizing the use of coordinated Polar
infrastructure for multi-platform science missions, while fos-
tering trans-disciplinary collaboration on Polar research. One
of the topics of the research is to improve satellite communi-
cation and navigation capabilities. In particular, the satellite
limitations will be studied, i.e., ionosphere effects, lack of
augmentation systems.
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TABLE 4. Summary of the national and international projects.
3) ARKKI PROJECT
The ARKKI project is conducted by the Finnish Geospatial
Research Institute in collaboration with the Finnish Min-
istry of Transport and Communications and aims to identify
the most significant challenges in navigation and geospa-
tial information-based applications in the Arctic region [51].
Within the project, the Action plan for the efficient deploy-
ment of satellite systems in Finland has already been pub-
lished, which defines the necessary steps for improving
positioning services in the Arctic [93].
4) ESA’s PROGRAM AND PROJECTS
To address positioning problems, the European Space
Agency (ESA) started supporting several projects within
ESA’s Discovery & Preparation program in 2019. One of
the projects, AMNAS [52], [95], aims to explore ways of
broadcasting navigation messages via satellites to vessels to
correct the vessel’s trajectories and support navigation in
the Arctic. The study is lead by Kongsberg Seatex, Space
Norway, and General Lighthouse Authorities of the United
Kingdom & Ireland [96].
In spring 2019, ESA allocated the NARWHALS project
funding [53], [97] in collaboration with SpacEarth Technol-
ogy, the primary objective to investigate solutions for more
robust, high-accuracy positioning in the Arctic regions, both
in shallow water and within ports. The project is oriented
at maritime applications, such as transportation, search and
rescue operations, research, and resource extraction activities.
Another project from ESA, the ArctiCom, aims to assess
the demands and offer communication solutions in the Arctic
region [54]. The assessment included many business sectors,
such as shipping, mining, oil and gas exploration, etc., and
geostationary and non-geostationary satellite communication
systems and terrestrial communication systems.
Another project, titled ‘‘5G-assisted Ground-based
Galileo-GPS receiver Group with Inertial and Visual
Enhancement’’ (5GIVE), carried out by the University of
Helsinki, is also funded by ESA and aims to develop the
methods of GNSS and terrestrial positioning signal fusion for
robust and seamless navigation [55]. The project’s objective
is to investigate how to combine the satellite positioning
techniques with motion sensors and terrestrial radio signals to
gain sufficient accuracy for the mission, even in challenging
environments, where satellite signals suffer from multipath
propagation.
IV. SIMULATION FRAMEWORK AND MAIN POSITIONING
SYSTEM OPERATION
A. POSITIONING SYSTEM OPERATION
As discussed before, the foremost positioning system in the
Arctic region remains the GNSS. Thus, we have conducted
a study to determine current satellite systems’ performance
in the Arctic from the autonomous vessel perspective.
We describe the current chapter’s simulation environment,
focusing on GNSS constellation analysis for the Arctic
region. The modeled systems include GPS, Galileo, and
GLONASS.
We assume that an autonomous vessel is operating in
the Arctic conditions. The vessel uses a dynamic position-
ing system with situational awareness sensors for collision
avoidance (CA), updating its position information with other
vessels using an AIS. In order to evaluate the considered
scenario, we have executed the simulation campaign.
B. SIMULATION ENVIRONMENT DESCRIPTION
The simulations were executed in several steps. First, as a
comparison between Arctic and non-Arctic regions, the Geo-
metric Dilution of Precision was analyzed based on 50,000
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FIGURE 2. Comparison of GDOP in Arctic region with GDOP values in non-Antarctic (right) and non-Arctic (left) regions for =10ominimum elevation
mask.
Monte Carlo simulations, looking at GDOP values based on
visible satellites with at least 10oelevation, i.e., the cut-off
elevation angle was set to 10o. The GDOP simulator was
built in Matlab, based on ephemeris data collected from a
Spectracom GSG-64 multiple constellation simulator with 64
channels, supporting all 4 GNSS (GPS, Galileo, GLONASS,
Beidou) systems. Only the geographical points above the
Arctic circle (i.e., above 66.56 North latitude) were consid-
ered, and user data was generated with a uniform distribution
along with the longitude values at latitudes above the Arctic
circle. The GDOP equation was based on [72] book and using
all satellites in view above the cut-off elevation angle.
Next, the comparison of GNSSs was made using an exten-
sive set of simulations with Systems Tool Kit (STK) [99].
In the simulations, the vessels were distributed through the
entire area of the Arctic region. In total, ten vessels were
distributed in the area of interest, covering the main shipping
routes. The simulated vessels were moving at the speed of
20 knots [100].
STK provides real models of the GNSS constellation. It
provides the GNSS almanacs that contain an up-to-date set of
data that every GNSS satellite transmits and includes infor-
mation, such as the state of the entire constellation and coarse
data on every satellite’s orbit. The repeat cycle of a satellite
constellation is when the entire constellation returns to the
initial position. While the repeat cycle of the entire GPS con-
stellations is equal to 1 sidereal day (approximately 23 hours
and 56 minutes), GLONASS and Galileo constellations will
return to the initial position in 8 and 10 sidereal days respec-
tively [69], [101]. We evaluated an entire ten-day period
and noticed that 48 hours is enough to capture a relevant
range of variation regarding satellites’ visibility in the region
of interest (see Fig. 3). Thus, the results achieved within a
48-hour period are used to analyze the maximum and the
minimum number of satellites. The period of the simulations
was from 20.02.2020 10:00 UTC to 22.02.2020 10:00 UTC.
V. NUMERICAL RESULTS
This section outlines the numerical results related to the
positioning accuracy of various systems and elevation angles.
A. GEOMETRIC DILUTION OF PRECISION
GDOP is a measure of the ‘goodness’ of the satellite geome-
try, and it is inversely proportional to the achievable position-
ing accuracy. Typical ‘excellent’ GDOP values are below 2
and ‘good’ GDOP values range between 2 and 5 [72]. The
results are shown in Fig. 2. Among the three considered
GNSS systems, GPS offers the best satellite geometry (i.e.,
the lowest GDOP), and Galileo offers the worst satellite
geometry in the Arctic region. While the average GDOPs
in the Arctic region is only slightly worse than the average
GDOP in the non-Arctic and non-Antarctic region, the best
(i.e., minimum GDOP) is significantly better outside the Arc-
tic region. The percentages of excellent GDOP (i.e., below 2)
are significantly lower for GPS and Galileo in the Arctic
region than the other considered regions in Fig. 2. GLONASS
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has comparative performance in GDOP in both Arctic and
non-Arctic regions. However, the percentages of excellent-
level GDOP for GLONASS are significantly lower than the
percentages of excellent-level GDOP for Galileo and GPS in
both Arctic and non-Arctic regions.
B. SATELLITE VISIBILITY COMPARISON
We have compared the GNSSs in terms of the visibility of
the satellites in the Arctic region. The simulation results are
presented in Table 5and show the satellite visibility during
the 48-hour period. The values presented in the table reflect
the satellite visibility from all ten vessels distributed in the
Arctic region. The single satellite coverage area is defined as
a region of the Earth where the satellite is seen at a minimum
predefined elevation angle [102].
TABLE 5. Satellite visibility for different GNSS.
In our simulations, the receiver shall have a clear view of
the sky, ensuring a direct LoS with as many visible satellites
as possible [103]. One of this study’s goals was to know the
vessels’ ability to locate themselves with different elevation
values varying from 10oto 30oin clear-sky conditions. The
value =10owas chosen as the minimum elevation angle for
the Arctic environment to prevent possible blockage caused
by natural barriers at the open sea, such as icebergs, or by the
vessel itself [4]. Then was increased up to 30oto simulate
possible LoS blockage caused by the port’s infrastructure.
At =30o, some of the systems have shown uncertain
performance, which is discussed further.
According to Fig. 3, GPS provides a maximum num-
ber of visible satellites for the lowest elevation angle (10o)
compared to other systems. However, by increasing the
receiver’s elevation angle, the GPS (as well as Galileo) is
reduced. The GLONASS system, however, can provide suf-
ficient coverage, even with the high elevation angles. Fig. 4
shows that more GLONASS satellites are present at some of
the time instants (20.02.2020 10:00-11:00 UTC, 20.02.2020
19:30-22:10 UTC, and 21.02.2020 6:00-8:30 UTC), which
may potentially result in better accuracy at that time. How-
ever, GLONASS shows equal performance as other GNSS for
other time instants. One of the explanations for these results
is that orbits of GPS, as well as Galileo constellations, are
more inclined from the Polar Regions. In general, it can be
concluded that the satellite visibility of all GNSSs is sufficient
FIGURE 3. Comparison of the GNSSs: 20.02.2020 10:00 UTC – 21.02.2020
10:00 UTC.
in the area of interest while having a maximum elevation
angle of less than 20o. However, such low elevation angles
might be a reason for the high noise level of satellite signals,
which can lead to the positioning accuracy reductions [4].
C. ARCTIC REGION POSITIONING ACCURACY EVALUATION
User accuracy refers to how close the device’s calculated
position is from the truth, expressed in meters. Fig. 5shows
the snapshot of the positioning accuracy of three GNSS
constellations, Galileo, GLONASS, and GPS, for the Arctic
Region. The snapshot is captured at 21.02.2020 07:17 UTC,
and it shows that the GLONASS system provides the highest
accuracy at this particular time. The positioning accuracy
calculation was performed by STK AGI software [104]. The
positioning accuracy (also referred to as Navigation Accuracy
by AGI developers) calculation is related to the Dilution of
Precision (DOP) in the definition of DOP with an assumption
of a single value for the uncertainty in the one-way range
measurement from the constellation. If four or more satellites
are in the ground receiver’s view, the receiver’s position and
the offset between the receiver clock and the GNSS clock are
being computed. During these measurements, the elevation
angle of the receiver is not taken into account. The accuracy
measurements take into account the geometry of the satel-
lite propagation and the uncertainty in the one-way range
measurements. The positioning accuracy varies dynamically
with time. The top row of snapshots of positioning accu-
racy are presented in Fig. 5. They show the accuracy varia-
tions between 0.9–2.7 meters for the systems’ standalone
operation. On average, for the entire period of simulations,
the GPS constellation provided 0.9 – 2.7 meters accuracy
range, the GLONASS provided the accuracy performance
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FIGURE 4. Number of visible satellite accesses from a single vessel,
elevation angle =30o: 20.02.2020 10:00 UTC – 21.02.2020 10:00 UTC.
of 0.9–2.5 meters, and the Galileo provided the accuracy
of 1 – 2.3 meters. For the autonomous vessel positioning,
the accuracy in the range of 1 – 3 meters in the open sea in
most cases is sufficient.
Many works propose utilizing an intelligent hybrid combi-
nation of different systems available on the node to increase
accuracy. Even though GLONASS appears to be the best
standalone candidate, coupling it with GALILEO and GPS
clearly shows the better results, see the bottom row in Fig. 5.
Here, we have modeled two scenarios: assisted and combined
operation modes. The assisted scenario presumes that the
vessel has been tracking its position constantly. Thus, it can
achieve a significantly higher level of precision by apply-
ing additional knowledge of the best positioning technology
accuracy in this area.
However, the vessel may face a rare situation when the
position should be estimated for the first time, e.g., after
reboot, initial launch, etc. In this case, a combined scenario
does not know the vessel’s approximate location. Generally,
it may be recommended to utilize, e.g., GLONASS for initial
calibration and switch to the assisted mode after it for better
accuracy.
VI. CHALLENGES AND FUTURE PERSPECTIVES
To improve positioning accuracy for autonomous vessels’
operations, we outline different strategies that shall be taken
into account in further studies.
A. HYBRID POSITIONING TECHNIQUES
The vessel’s autonomy level will depend on the vessel type,
size, and operational environment. The more complex the
autonomous vessel’s mission is, the more strict requirements
it will have to the positioning systems. Extensive work has
already been done on the existing solutions to add positioning
and collision avoidance redundancy in the autonomous vessel
operation [8], [39]–[44]. For example, the hybrid positioning
techniques may include land-based external reference sys-
tems for aided navigational reliability when operating in the
proximity of the shore. Land-based cameras and radars can be
used to navigate the vessel along the shore safely. As GNSS
FIGURE 5. The snapshot (21.02.2020 07:17) of positioning accuracy of the
Galileo, GLONASS, and GPS constellations. The data is obtained using the
simulation environment STK: Coverage module [105].
may not always be available and sufficient, the cellular-based
positioning techniques can also be useful when available [45].
B. SENSOR FUSION
Several methods are used to determine the position of an
autonomous vehicle or a vessel. Those methods include vari-
ous communication technologies such as ITS-G5, WiFi, LTE,
etc., as well as cameras, radars, and physical landmarks [39].
The location can be determined through the sensor fusion of
several technologies.
C. COMBINATION OF EARTH OBSERVATION DATA WITH
GNSS AND COMMUNICATION SATELLITES
The satellites’ observation data can help determine the chal-
lenges on terrestrial or marine vehicles’ routes in real-time.
Like this, the sea ice maps can be created and sent to the vessel
to reduce the possible damage caused by heavy ice. A combi-
nation of Earth observation data and terrestrial observations
and weather conditions will provide the best possible traffic
conditions for terrestrial vehicles. One method of obtaining
the observation data is available as part of the Copernicus
Earth observation program. However, the program is still in
the early stages, and only a small part of the data is available.
Some of the advantages of integrated EO techniques with
positioning satellites were described previously by a Polaris
study from ESA [106] and in a study from the Ministry
of Transports and Communications [107]. The Internet of
Things (IoT) applications can serve as a great example of
the combination of GNSS, EO, and communication satel-
lites bringing together improved connectivity, geoposition-
ing, and image data [79]. Another example of a combination
of satellite systems is crowd-sourcing: users in the Arctic
regions can provide geolocated information about the current
region (such as unexpected weather conditions, wildlife, sea
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TABLE 6. Summary of the Arctics positioning challenges and possible solutions.
conditions, local environment monitoring). These data can
help to build a complete picture in the region of interest.
In [5], an example is given about how crowd-sourcing can
provide information on the sea depth to create the depth maps
using the vessels’ data.
D. SMALL SATELLITE CONSTELLATIONS OR SWARMS
Small satellites gain popularity to overcome the lack of
communications in remote areas due to their small size
and, thus, the relatively more straightforward launching
process. However, the small-satellite communication sys-
tem experience challenges with station keeping. It has been
proven that by using the small-satellite swarms, the aver-
age end-to-end time can be significantly reduced [108].
These small satellite systems can be considered a solution
to support time-limited missions or transmission of recorded
data regularly, thus improving environmental awareness and
navigation in this region. Moreover, small satellites uti-
lize GNSS, allowing them to more effectively locate air-,
marine-, and terrestrial vehicles indirectly. Small satellites
can correct GNSS positioning inaccuracies caused by iono-
spheric disruptions. If larger constellations of small satellites
are deployed, the guiding of autonomous vehicles can be
made efficiently [93].
E. QUANTUM TECHNOLOGIES
In the future, satellites may be using Quantum technologies
that could also provide benefits to Arctic regions. Such advan-
tages include different applications, such as Quantum Key
Distribution (QKD) for systems and services encryption, iner-
tial navigation, gravity measurements, and many more [109].
F. SIMULATION CAMPAIGNS
Finally, vessel and satellite system simulations could also
significantly assist in achieving additional improvements; an
example of such simulations was provided in the current
work. The comparative modeling can provide useful initial
information about the existing GNSSs and their performance
in the Arctic. However, long-term simulations and more
detailed analyses are needed in the future, thus, bringing the
need to combine various techniques in one system efficiently.
That would include defining the requirements for accuracy of
positioning for certain ship types in selected places and deter-
mining whether GNSSs alone or joint constellation could
support certain operations. It is also essential to understand
how different techniques, such as the use of pseudolites and
the use of L-Band correction data, may improve positional
accuracy [110].
VII. SUMMARY
To improve GNSS positioning in the Arctic region is an
interest sustained by several ongoing research and industrial
activities in the current region, the North Pole is a place of
potential to explore natural resources. Based on the extensive
review, we have outlined the main projects currently executed
in this field, highlighting the most significant challenges and
the corresponding potential solutions as recommendations for
other researchers in Arctic navigation systems development.
As a baseline, we have modeled and compared existing
GNSS constellations and studied the Arctic positioning for
the autonomous vessels. The simulation campaign consisted
of identifying geometric dilution of precision and the satellite
visibility in the Arctic. The simulations have shown sufficient
visibility of the GNSS satellites, considering low minimum
elevation angles at the receiving antennas and the accuracy of
fewer than three meters in all studied constellations. However,
the visibility of satellites in a single system can be limited at
high minimum elevation angles. Accurate positioning can be
achieved by the simultaneous utilization of several position-
ing systems.
ACKNOWLEDGMENT
This article is an extended version of work by Anastasia
Yastrebova et al. ‘‘Comparative Study on GNSS Positioning
Systems for Autonomous Vessels in the Arctic Region’’, Pub-
lished in WiP Proceedings of the International Conference on
Localization and GNSS (ICL-GNSS 2020), Vol. 2626, p. 12,
CEUR (CC BY 4.0), 2020.
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ANASTASIA YASTREBOVA received the M.Sc.
degree in information technology from Tampere
University (former Tampere University of Tech-
nology), Finland, in 2019. She is currently pursu-
ing the Ph.D. degree with the University of Oulu,
Finland, with a focus on satellite communications.
She is also a Research Scientist with Technical
Research Centre of Finland VTT Ltd. Her research
interests include heterogeneous wireless commu-
nication networks and next-generation communi-
cation systems for remote monitoring and autonomous operation of on-land
and maritime systems.
MARKO HÖYHTYÄ (Senior Member, IEEE)
received the D.Sc. (Tech.) degree on telecom-
munication engineering from the University of
Oulu, where he currently holds adjunct profes-
sor (docent) position. Since 2005, he has been
with VTT Technical Research Centre of Finland
Ltd. in various researcher and team leader posi-
tions. He is currently working as a New Space
Co-Creation Manager, coordinating space technol-
ogy research at VTT. He was a Visiting Researcher
at the Berkeley Wireless Research Center, CA, from 2007 to 2008, and a Vis-
iting Researcher with the European Space Research and Technology Centre,
the Netherlands, in 2019. He has published over 70 scientific articles and he
is an Invited Speaker in events, such as Critical Communications World and
Autonomous Ship Technology Symposium. His research interests include
critical communications, autonomous ships, and resource management in
terrestrial and satellite communication systems. His Google Scholar h-index
is 18.
SANDRINE BOUMARD received the Master of Science and Master of
Advanced Studies degrees in electronics, systems, and radar and radio-
communication from the Institut National des Sciences Appliquées (INSA),
Rennes, France, in 1998. She has been working at VTT. She is currently
a Senior Scientist with the Autonomous Systems Connectivity Team in the
connectivity research area of the knowledge intensive products and services
business area at VTT. She has been involved in several research and devel-
opment projects, national, and international projects. She has coauthored
several conference and journal papers as well as book chapters. Her research
interest includes physical layer algorithms, such as positioning, synchroniza-
tion, and OFDM systems, but her experience ranges from channel modeling
to system level analysis and simulation as well as VHDL modeling.
ELENA SIMONA LOHAN (Senior Member,
IEEE) received the M.Sc. degree in electrical
engineering from the Polytechnic University of
Bucharest, Romania, in 1997, the D.E.A. degree
(French equivalent of master) in econometrics
from Ecole Polytechnique, Paris, France, in 1998,
and the Ph.D. degree in telecommunications from
the Tampere University of Technology, in 2003.
She is currently a Professor in electrical engineer-
ing unit with Tampere University (TAU), Finland,
and the Coordinator of the MSCA EU A-WEAR network. Her current
research interests include wireless location techniques, wearable computing,
and privacy-aware positioning solutions.
ALEKSANDR OMETOV (Member, IEEE)
received the D.Sc. (Tech.) degree in telecommu-
nications and the M.Sc. degree in information
technology from the Tampere University of Tech-
nology (TUT), Finland, in 2018 and 2016, respec-
tively, and the Specialist degree in information
security from Saint Petersburg State University
of Aerospace Instrumentation (SUAI), Russia,
in 2013. He is currently a Postdoctoral Research
Fellow with Tampere University (TAU), Finland.
He is also working on H2020 MCSA ITN A-WEAR and APROPOS projects.
His research interests include wireless communications, information secu-
rity, blockchain technology, and wearable applications.
53978 VOLUME 9, 2021
