Review Article
Evolution of Indoor Positioning Technologies: A Survey
Ramon F. Brena,
1
Juan Pablo García-Vázquez,
2
Carlos E. Galván-Tejada,
3
David Muñoz-Rodriguez,
1
Cesar Vargas-Rosales,
1
and James Fangmeyer Jr.
1
1
Tecnol
´
ogicodeMonterrey,Av.E.GarzaSada2501,64849Monterrey,NL,Mexico
2
Facultad de Ingenier
´
ıa,MyDCI,UniversidadAut
´
onomadeBajaCalifornia,Av.
´
A. Obreg
´
on S/N, 21100 Mexicali, BC, Mexico
3
Programa de Ingenier
´
ıa de Soware, Universidad Aut
´
onoma de Zacatecas, Av. Begonias 2, 98000 Zacatecas, ZAC, Mexico
Correspondence should be addressed to Juan Pablo Garc
´
ıa-V
´
azquez; pablo.garcia@uabc.edu.mx
Received 13 October 2016; Revised 22 January 2017; Accepted 21 February 2017; Published 29 March 2017
Ac
ademic Editor: Alberto J. Palma
Copyright © Ramon F. Brena et al. is is an o pen access article distributed under the Creative Commons At tribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Indoor positioning systems (IPS) use sensors and communication technologies to locate objects in indoor environments. IPS
are attracting scientic and enterprise interest because there is a big market opportunity for applying these technologies. ere
are many previous surveys on indoor positioning systems; however, most of them lack a solid classication scheme that would
structurally map a wide eld such as IPS, or omit several key technologies or have a limited perspective; nally, surveys rapidly
become obsolete in an area as dynamic as IPS. e goal of this paper is to provide a technological perspective of indoor positioning
systems, comprising a wide range of technologies and approaches. Further, we classify the existing approaches in a structure in order
to guide the review and discussion of the dierent approaches. Finally, we present a comparison of indoor positioning approaches
and present the evolution and trends that we foresee.
1. Introduction
Position location of a user or a device in a given space is one
of the most important elements of contextual information.
e widespread use of sensors has produced an increasing
wealth of such information. By itself, location has generated
greatattentionbecauseofitspotentialtoleveragecommercial
applications such as advertisement and social networks [].
e user context, constituted by all relevant items surround-
ing her/him, has been given paramount importance in the
design of next-generation information systems and services.
e adaptation to a changing context is precisely what makes
those next-generation systems exible and robust [].
Location detection has been very successfully imple-
mented at outdoor environments using GPS technology [].
e GPS has made a tremendous impact on our everyday lives
by supporting a wealth of applications in guidance, mapping,
andsoforth[].Nevertheless,inindoorenvironments,the
usabilityoftheGPSorequivalentsatellite-basedlocationsys-
tems is limited, due to the lack of line o f sight and attenuation
of GPS signals as they cross through walls. Indeed, precision
of some meters inside a commercial setting is useless
with respect to a task such as locating specic merchandise
on a shelf. us, the need for specialized methods and
technologies for indoor location systems (also called indoor
positionin g systems, IPS) has been widely accepted [–].
ManysurveyshavebeenwrittenbasedonvariousIPS
relatedtopics[–].However,mostofthemomitseveral
relevant technologies, have a limited perspective, or lack a
classication structure. For instance, the use of visible light
[–]orEarth’smagneticeld[,]hasbeenoverlooked
in some reviews (see Table ). Also, the lack of a classication
scheme that would guide the readers in a clean way is a serious
aw of some otherwise good surveys []. Furthermore,
an updated survey in indoor positioning systems is always
welcomeasthisisarapidlyevolvingareaandadecade-old
review can be considered outdated.
In this survey, we review the eld of indoor positioning
systems (IPS) because it presents specic features, challenges,
and opportunities. Indoor settings are mostly full of obstacles
that obstruct the signals between emitters and receivers,
and a wide variety of materials, shapes, and sizes aect
signal propagation more than in outdoor scenarios. IPS face
an interesting technical challenge due to the great variety
Hindawi
Journal of Sensors
Volume 2017, Article ID 2630413, 21 pages
https://doi.org/10.1155/2017/2630413
Journal of Sensors
T : Previous surveys comparison, including ours. “Passive” means that the infrastructure generates the signal and that the object or
person to be located receives it.
Technology or feat ure Liu Gu Mautz Deak Koyuncu Ours
Infrared mobile reader No Yes No No No Yes
Infrared badge Mention Yes Yes Yes Yes Yes
Laser (passive) No No Yes No No No
Ultrasound passive No Yes Yes No Yes Yes
Ultrasound active Mention Yes Yes Yes Yes Yes
Audible sound active No Yes Yes No No Yes
Audible sound passive No No No No No Yes
Audible sound ambient No No No No No Yes
Magnetic generated No Yes Yes No No Yes
Magnetic ambient No No Yes No No Yes
RFID mobile tag Yes Yes Yes Yes Yes Yes
RFID mobile reader No No Yes No No No
Wi-Fi Yes Yes Yes Yes Yes Yes
Bluetooth Yes Yes Yes Yes No Yes
ZigBee No No Yes No No Yes
UWB Yes Yes Yes Yes Yes Yes
Tomographic (water resonance) No No No Yes No No
Cameras infrastructure Mention Yes Yes Yes Yes Yes
Cameras (portable) No No Yes No No Yes
Floor tiles No No Yes Yes No No
Air pressure No No Yes Yes No No
Inertial No No Yes Mention Yes Yes
Ambient light No No No No No Yes
Articial light (no encoding) No No No No No Yes
Articial light (encoded) No No Yes No No Yes
Indoor AGPS, pseudolites Yes No Yes No Yes Yes
Cellular Yes No Yes Mention Yes Yes
TV, FM No No Yes Yes No Yes
Classication-guided Partial Partial No Yes Partial Yes
of possible sensor technologies that can be applied, each
one with dierent strengths and weaknesses. e focus of
this particular survey is precisely on reviewing the dierent
technologies that have been used for IPS. We present a
comprehensive review of the literature on indoor positioning
systems, with the goal of providing a technological per-
spective of IPS evolution, making the distinction between
dierent technological approaches by using a classication
scheme, and presenting the evolution and trends of the eld.
We stress that although outdoor positioning techniques
couldbeusedinindoorenvironments,theseareleoutofour
scope because this survey is specialized specically in indoor
technologies.
ispaper’sstructureisasfollows:aerthisintroduction,
we compare this survey with other ones, to justify its publi-
cation; then, in Section , we present the methods and issues
related to the eld itself. en, in Section , we proceed to
present the review of indoor positioning technologies, which
is the main subject of this report. Aer t hat, Section presents
a comparison of location technologies. Finally, in Section ,
we present a discussion, forecasting the possible evolution
that indoor positioning systems will have in the years to come,
and some conclusions.
2. Related Work
ough, as mentioned befo re, many IPS surveys have been
published [–, –], we can see that some surveys such
as Hightower and Borriello’s [ ] are just outdated for a
rapidly changing area such as IPS. Also, some otherwise good
reviews lack a classication scheme that would allow the
reader to organize the dierent works in some conceptual
structuremoreusefulthanaatandanunorganizedlist.
e most representative example of this aw is the oth-
erwise very good review by Mautz [], w here a at list
of technologies is presented in a sequential order, with
no classication whatsoever. In our paper, we introduce
thorough classication criteria that will partition the set of
dierent works, making it more manageable and providing a
conceptual structure for mapping the IPS eld. Furthermore,
some classication schemes proposed in previous reviews
are not sound; for instance, Gu et al. [] classied IPS
Journal of Sensors
systems as network-bas ed, systems that take advantage of
existing network infrastructure, and non-network-based, sys-
tems using infrastructure solely dedicated to positioning,but
this leav es no space for purely passive systems, like magnetic
eld ngerprinting or ambient light analysis, as well as other
technologies like image analysis.
One can also see that most reviews that strive to be
comprehensiveomitentiretechnologies,nottomention
individual works. For instance, Gu et al. [] omitted inertial
navigation, ambient magnetic ngerprinting, the use of
encoded patterns in art icial light (uorescent or LED),
ambient light analysis, the use of audible sound transmitted
by the infrastructure (some with encoded patterns), RFID
wherethetagsarexedandthereaderismobile,ZigBee,
vision analysis with portable cameras, oor tiles, and the
indoor use of outdoor technologies (GPS, cellular, TV, and
FM signals).
InTable,wepresentthetechnologiesreviewedinseveral
prominent technology-oriented surveys, compared with this
survey. In the table, we write “mention” to indicate that
the survey does not include a complete discussion of the
corresponding technology. As the reader can see in this table,
even current, supposedly comprehensive surveys like Deak’s
omit een dierent technologies.
We stress the fact that very broad technology names are
not t as organizing principals in an IPS survey because
the applications of a broad technolog y can be very creative
and dieren t. For instance, “magnetic” technologies include
both those which pick up the irregularities of Earth’s natural
magnetic eld and those which generate a pulsating magnetic
eld that will be registered by a sensor; these are completely
dierent technologies. us, saying that a given survey
covers “magnetic elds” is not precise enough. Some reviews
intentionally leave out some areas. Liu et al.’s review [] only
considers wireless-based positioning systems, thus leaving
out inf rared, vision-related systems, sound or ultrasound,
inertial systems, ambient light, oor tiles, and magnetism
analysis (infrared and ultrasound are briey men tioned in a
section about “Positioning Using Multiple Media”).
Finally,somesurveyshavenotfocusedontheuseof
technologies as this one does. For example, Sun et al. []
analyzed location algor ithms, not technologies. In the case of
the very comprehensive Mautz survey, we stress the fact that
it has a slightly dierent character inherent in the fact that it is
primarily a thesis and not a journal publication. Please refer
to Table for a detailed comparison.
In Table , “passive” means that the infrastructure gen-
erates the signal and that the object or person to be located
receives it. For instance, “ultrasound passive” means that
the device the user is carrying receives sound generated
from the infrastructure and calculates the position from that
information. Sometimes we write “portable” or “mobile” for
“passive,” as in “cameras (portable),” to emphasize the fact
that the user is carrying the camera. Indeed, the distinction
between active and passive is pervasive to many technologies
and is one of the classication criteria we used; in the case
of RFID, we cannot use the terms “passive” and “active”
to indicate which end of the communication is the reader
because the terms “active” and “passive” have another very
specic meaning in the context of RFID. Another distinction
is between signals with embedded encoded information
and signals without embedded encoded information, where
the former include some method of attaching symbolic
information to the carrying signal in such a way t hat the
receiver decodes the signal and recovers that information.
3. Location Methods and IPS
In general terms, a location estimation consists of an algo-
rithm with three stages. e rst stage is the evidence,where
devices involved measure characteristics of a signal. e
second stage is the range estimation,wheredevicesusethe
measurements or evidence obtained to estimate distance
to/from the object that needs to be located. e third stage
is the combination of such range estimates in order to
estimate position. is combination could be carried out
using optimization methods (see []) or matrix equation
methods (see [, ]), among other techniques. In this
section, we present the most common techniques use d to
locate a user/object in indoor environments.
We will use the term position to emphasize the notion of a
point in a coordinate system, whereas place will emphasize a
region in a given context, for example, “living room”; location
could refer to both. Indoor positioning systems (IPS, also
“indoor location systems”) thus provide information about
the place where a user or object is situated in an indoor
environment.
An IPS estimates the target object location from the
obser vation data collected by a set of sensing devices or
sensors []. An indoor location system can report the
estimation as a symbolic reference, for instance, “kitchen,”
or as a coordinate-based reference []. Positions could be
given in a number of dierent coordinate systems, depending
on the purpose of the application. For instance, in outdoor
navigation systems, the latitude and longitude are associated
with a spherical coordinate system, but, for indoor location,
generally a at Cartesian coordinate system is better suited.
In any case, a coordinate system transformation is always
possible, so this is not one of the most crucial issues.
In this paper, we make the distinction between techniques
and technologies, where the term “technique ” refers to some
basic abstract tool, not necessarily tied to physical media,
whichinprinciplecouldbeusedinseveral“technologies”;
technologies are specic ways of using physical signals,
registered through sensors, like radio waves or magnetic
elds, in order to accomplish the goals of an IPS.
Multilateration basically uses geometry to combine the
range estimates from dierent reference devices [, , ].
e range estimates could come from dierent measure-
ments such as RSS (Received Signal Strength), ToA (Time
of Arrival), TDoA (Time Dierence of Arrival), and AoA
(Angle of Arrival). If three reference devices are used in the
combination, then it is called trilateration.
Time of Arrival (ToA) is sometimes called Time of Flight
(ToF); it is the time taken by the signal to go from the
transmitter to the receiver. If the receiver is able to obtain
as evidence ToA, say 𝑡
0
,thenitwillestimaterange𝑑 by
using the speed of light 𝑐=3×10
8
m/s with 𝑑=𝑐𝑡
0
.
Journal of Sensors
A
B
C
P
R2
R3
R1
(a)
X
Transmitter 1
Y
Transmitter 2
Transmitter 3
A
B
(b)
F : Time measures (a) ToA and (b) DToA.
en, several reference devices combine their range estimates
[]. From the multilateration point of view, ToA describes
circles around the reference devices (see Figure (a); this
gure, as well as the following thr ee, is similar to the ones
in Liu et al.’s survey []), and although two circles are
sucient to solve for the coordinates, a third one is needed
to get rid of the ambiguity. Normally, for the conguration
in Figure (a), A, B, and C will be the transmitters and P will
be the receiver, as is the case in GPS applications; this setting
allows keeping the location of P private. As there could be
errors in the ToA measures, either small ones due to noise
and measurement precision or large ones due to reections,
multipath, or scattering of the signal, we will not be able to
determineasinglepointasthesolution,butaregion,ofwhich
we normally select the point considered as the best guess.
In the context of IPS, some of the problems with ToA will
beaggravated:rst,whileinGPSthesatellitepositionsare
knowninadvancebytheirorbitalparameters,inIPS,thisis
not the case, because there is not a general agreed reference.
Second, for very short distances as are indoor ones, for RF
signals, the time dierences will be extremely small, so great
precision is needed.
Time Dierence of Arrival (TDoA) is related to ToA in
the sense that it uses the travel time from the transmitter to
the receiver in order to estimate distances, but sometimes the
emitting time is unknown; thus, the dierence in travel times
from each receiver is used to estimate the distance to each
of them. e calculation of the time dierence eliminates the
need for the time of transmission to be known []. As in
ToA or any other time-based method, synchronicity between
devicesmustbeachievedtohaveaccuratemeasurements.
However,sinceTDoAdoesnotusethedistancebetweenthe
transmitter and the receiver, the transmitter is not required
to be in sync with the receiver. Synchronicity is only required
between a ll receivers, since the calculation is based on their
time/distance dierence [].
Angle of Arrival (AoA) provides a measurement of the
angleatwhichasignalisreceivedinareferencedevice.
A
B
P
𝜃
1
𝜃
2
F : AoA measure.
e reference device denes a line that departs from its
position with such angle measured, where the target object is
assumed to be. e combination of several lines from several
reference devices places the target object at the intersection of
several lines. At least two reference points and two angles are
used (𝜃
1
, 𝜃
2
) (see Figure ). e advantage of this measure is
that no time synchronization is required between references.
e disadvantage is that it requires complex hardware to
determine AoA [].
Received Signal Str en gth (RSS) is the eld intensity of
a signal at the receiving point. RSS is measured at the
receiver (see Figure ), and then distance could be estimated
by using a signal propagation model [, ] or other
methods. In particular, the Friis pr opagatio n eq uation is
oen used []; at other times, more complex models are
considered. e RSS technique requires t he use of multila-
teration.
Journal of Sensors
A
B
C
P
LS
1
LS
3
LS
2
F : RSS measure.
Proximity techniques consist of determining when an
object is “close” to a known location, as registered by a sensor
specically aimed at detecting proximity. ere are two main
approaches to sensing proximity: (i) detecting an object with
a physical contact through touch sensors, capacity sensors,
and so forth or (ii) detecting an object in a range area of one
or more remote identica tion systems such as Bluetooth and
RFID cards [].
Fingerprinting is a method used to calculate approximate
locations. e term has been used especially as a way to
obtain locations from the detection of Wi-Fi signals and
the like, as these are registered at a mobile device, but it
is a general technique that has been used for Bluet ooth
andmagnetismaswell.Itiscomposedoftwophases:
training and position determination. In the training phase, a
radio map of observed signal strength values from dierent
locations is recorded. en, in the position determination
phase, the signal strength values observed at a user device
are compared to the radio map values using proximity
matching algorithms, such as 𝑘-nearest neighbor (𝑘-NN),
in order to infer current user location [], together with
interpolation.
Very oen, it is necessary to compensate for signal propa-
gation impairments and the presence of noise in the measure-
ments. is can be done using forms of aggregating partially
redundan t signals over a lapse of time. Some of the most
useful smoothing methods are carried out by digital adaptive
lter algorithms [] such as Kalman [] and particle []
lters.
e Kalman lter [] is useful for smoothing noisy data
bytakingasequenceofnoisyvaluesandestimatingthevalue
of the underlying variables more reliably.
In the context of location systems, particle ltering
involves creating a “cloud” of estimated position points called
particles,usingsomeprobabilitydistributionaroundthe
believed actual position. When a movement takes place, dis-
placement is applied to all particles at each “prediction” step.
e relation between the transformation and the new particle
positions requires the application of a model, which is appli-
cation dependent. en, a resampling step evaluates the t-
ness of each particle with respect to the new observations, so
that unt particles are destroyed and new particles are created
near the best t particles; eventually, the weights of particles
areupdatedaswell.isprocessisrepeatedinaniterativeway
[].
Regardless of the specic details, many location tech-
nologies face the following challenges; t he severity of each
challenge varies from one technology to another.
Signal Propagation.Mostmethodsandalgorithmsusedto
locateobjectsarebasedonsignalpropagation,asisthecase
for electromagnetic signals and sound. As they propagate,
their power is gradually reduced (“attenuated”), following
well-known physical laws [, , ]; the signal attenuation
is normally measured in decibels (dB) logarithmic scale.
Asthesignalgetsweakerasthedistancefromthesource
increases, the signal-to-noise ratio gets worse. D uring its
travel, the signal could also encounter obstacles and density
changes, and so it is aected by propagation impairments
such as reections, scattering, and interference, becoming
more dicult to measure with sensing instruments.
Multipath Environment. Signals can become mixed with some
of their reections, causing them to b e scrambled and dicult
to r ecognize. Another associated problem is that when a
sensor receives a signal, it might not come from a line-of-sight
path; hence, the total distance traveled by the signal is greater
than the direct path. is can cause an error in the distance
estimation and hence an error in the location estimation.
Line of Sight. Some of the location technologies require a
nonobstructed path between a transmitter and a receiver,
which is called line of sig ht (LOS). If LOS is required, the
transmitterandthereceivermusthaveacleartrajectorythat
avoids obstructions [].
Synchronization. For some of the techniques used in IPS, it is
required to have several clocks in very precise synchroniza-
tion: for ToA, the signal travel time is taken from the time
dierence between the transmitter and the receiver clocks,
whereas in TDoA we need to me asure with much precision
the dierence between the clocks of two receivers [].
4. Indoor Positioning Technologies
Before introducing the technologies, we introduce a classi-
cation to provide useful structure to an otherwise tangled
mass of references. We classify IPS technologies using several
criteria, one of which is the kind of signal used for location.
We can have the following kinds of signals:
(i) Radio F requency Signals (RF). A very generic term
relatedtothefrequencyofradiosignals,usedinmany
popular communication protocols such as Wi-Fi and
Bluetooth []. RF signals for indoor environments
considered are in the MF (medium frequency, around
MHz) range, particularly between and GHz.
(ii) Light.Bothvisibleandinfraredlight.Althoughthisis
an electromagnetic signal just as the RF signals, the
associated technologies are quite dissimilar.
(iii) Sound.Bothaudibleandultrasonic.
(iv) Magnetic Fields.BothnaturalEarth’smagneticeld,
along with its irregularities, and articially produced
magnetic elds.