Department of Science and Technology Institutionen för teknik och naturvetenskap Linköping University Linköpings universitet

gnipökrroN 47 106 nedewS ,gnipökrroN 47 106-ES

LiU-ITN-TEK-A-14/034--SE

Comparison and implementationof IPS

Dan Helgesson

Emelie Nilsson

2014-08-26

LiU-ITN-TEK-A-14/034--SE

Comparison and implementationof IPS

Examensarbete utfört i Elektroteknikvid Tekniska högskolan vid

Linköpings universitet

Dan HelgessonEmelie Nilsson

Handledare Jingcheng ZhangExaminator Qin-Zhong Ye

Norrköping 2014-08-26

Upphovsrätt

Detta dokument hålls tillgängligt på Internet – eller dess framtida ersättare –under en längre tid från publiceringsdatum under förutsättning att inga extra-ordinära omständigheter uppstår.

Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner,skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat förickekommersiell forskning och för undervisning. Överföring av upphovsrättenvid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning avdokumentet kräver upphovsmannens medgivande. För att garantera äktheten,säkerheten och tillgängligheten finns det lösningar av teknisk och administrativart.

Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman iden omfattning som god sed kräver vid användning av dokumentet på ovanbeskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådanform eller i sådant sammanhang som är kränkande för upphovsmannens litteräraeller konstnärliga anseende eller egenart.

För ytterligare information om Linköping University Electronic Press seförlagets hemsida http://www.ep.liu.se/

Copyright

The publishers will keep this document online on the Internet - or its possiblereplacement - for a considerable time from the date of publication barringexceptional circumstances.

The online availability of the document implies a permanent permission foranyone to read, to download, to print out single copies for your own use and touse it unchanged for any non-commercial research and educational purpose.Subsequent transfers of copyright cannot revoke this permission. All other usesof the document are conditional on the consent of the copyright owner. Thepublisher has taken technical and administrative measures to assure authenticity,security and accessibility.

According to intellectual property law the author has the right to bementioned when his/her work is accessed as described above and to be protectedagainst infringement.

For additional information about the Linköping University Electronic Pressand its procedures for publication and for assurance of document integrity,please refer to its WWW home page: http://www.ep.liu.se/

© Dan Helgesson, Emelie Nilsson

Abstract

Indoor positioning systems can advantageously be used in many applications, from hospitals to airportsand supermalls. This thesis cover many components necessary to construct an Indoor Positioning System(IPS), and even a solution of how it can be done.

The thesis includes different techniques used for measurements, based at for example Received SignalStrength Indication (RSSI) or dead reckoning. It also includes different positioning techniques used whenmeasurements are taken. Fingerprinting and triangulation are, among others, techniques that are to bedescribed. The most common technology to design an IPS upon is WiFi or Bluetooth Low Energy (BLE),but in this thesis the ZigBee technology is used to construct an IPS solution.

The designed system, ZBeacon, is described and evaluated in the second part of this thesis. The systemis composed of two integrated systems: a Radio Frequency (RF) solution based on devices from the companyWiotech and accelerometer data from a mobile phone. An estimated position is calculated with trilaterationbased on RSSI measurements together with data from the accelerometer, and an accuracy of 3.33 m isachieved.

Contents

I Background study 4

1 Introduction 4

2 Measurement techniques 42.1 Received Signal Strength Indication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.2 Angle of Arrival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.3 Dead Reckoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.4 Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3 Positioning Techniques 73.1 Topologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.2 Location estimation algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.3 Fingerprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.4 Trilateration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123.5 Multilateration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.6 Triangulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.7 Cell of Origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

4 Technologies 164.1 Bluetooth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164.2 WLAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174.3 Radar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174.4 ZigBee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184.5 GNSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184.6 RFID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194.7 Camera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194.8 Ultrasound . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204.9 GSM/UMTS/LTE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

5 Summarization of already existing systems 21

II ZBeacon 22

6 Indoor Position System 226.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226.2 Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226.3 System Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

6.3.1 Device tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256.3.2 System tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

6.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286.4.1 Device tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286.4.2 System tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

7 Discussion 37

8 Conclusion 38

9 Future work 39

1

List of abbreviations

AoA Angle of Arrival.

AP Access Point.

BLE Bluetooth Low Energy.

CoO Cell of Origin.

CSMA/CA Carrier Sense Multiple Access/Collision Avoid-ance.

CW Continuous-Wave.

FMCW Frequency-Modulated Continuous-Wave.

GPS Global Positioning System.

GSM Global System for Mobile Communications.

IPS Indoor Positioning System.

LAN Local Area Network.

LED Light-emitting diode.

LOS Line of Sight.

LTE Long-Term Evolution.

M2M Machine to Machine.

NFC Near Field Communication.

OAoA Optical Angle of Arrival.

PAN Personal Area Network.

RF Radio Frequency.

RFID Radio-frequency Identification.

RSSI Received Signal Strength Indication.

RTLS Real Time Locating System.

SSR Secondary Surveillance Radar.

TDOA Time Difference of Arrival.

TOA Time of Arrival.

UMTS Universal Mobile Telecommunications System.

2

VLC Visible Light Communication.

WLAN Wireless Local Area Network.

3

Part I

Background study

1 Introduction

The ability to navigate has been of great importance in the cultivation of the modern world. The mostwidespread positioning system is the Global Positioning System (GPS). Unfortunately GPS has poor cover-age indoors, and that is why the research about similar systems to be used indoors is a hot topic in recenttimes.

There are several different techniques used for the construction of an Indoor positioning system (IPS),and the applications are even more. In time of writing, there is no universal positioning system for indoorusage, that performs good accuracy independent of environment and application.

This thesis is subdivided into two parts: Part I present different useful techniques and technologiesused for construction of an IPS. It treats pros and cons of the most common techniques and includes asummarization of existing IPSs. Out from what is presented and learned in the first section, an IPS isdesigned, implemented and evaluated. This is what the second part describes.

2 Measurement techniques

There are different types of measurements that can be used in an IPS. The four most relevant measurementtechniques for RF devices are presented in this chapter. Combining those techniques can advantageouslyenhance the accuracy of the measurements.

2.1 Received Signal Strength Indication

In most RF-transceivers the signal power can be measured. A measurement of the power presented in areceived signal is often called RSSI. The original purpose was to measure if the signal strength betweendevices was sufficient, but that does not prevent engineers from using it to estimate distances. The RSSImeasurements are implemented in different ways for every device which the authors of [1] indicate as aproblem, especially when using Wi-Fi chipset for distance measurements. The authors also state that thespectrum around 5 GHz is more stable than 2.4 GHz for RSSI measurements, which is logical since the 5GHz-band is less used. As is well known, interference is an actual problem in wireless communications. RSSIcan be inaccurate since the device sees no difference between signals arriving directly from the source, andnoise. Therefore interference affects the RSSI value in an additive way, which means that large interferencewill decrease the accuracy of an IPS based on RSSI. The author of [2] has demonstrated that performanceof measurements can be enhanced, even in somewhat noisy environments. When RF signals travels throughwalls and obstacles the signal attenuation becomes dependent on more than distance, which is a problemwhen estimating distances.

2.2 Angle of Arrival

Angle of Arrival (AoA) measurement is a technique where the direction of propagation of a RF wave isdetermined. To measure the AoA usually two or more antennas are used. The most logical way to measureAoA is to use a receiver with an array of antennas. More antennas will result in higher accuracy. The TimeDifference of Arrival (TDOA) between the antennas will entail a phase difference, which can be convertedto an angle measurement. An alternative solution is to take advantage of one or several rotating antennasmeasuring RSSI, which the authors of [3] demonstrates.

4

Table 2: Expected position error depending on angle inaccuracy

Angle error Acceleration Position at Position at(degree) (m/s/s) 10s (m) 1 min (m)

0.1 0.017 1.718 61.8660.5 0.086 8.592 309.3261 0.172 17.184 618.6282 0.344 34.363 1237.1

2.3 Dead Reckoning

Dead reckoning is based on calculations with three parameters: distance, direction and time. The positioncan only be calculated if the previous position or the primary position is known. Dead reckoning is not oftenused as a standalone measurement technique when constructing an IPS, usually it is used as a complementto other techniques. Accelerometers, gyroscopes and magnetometers are typical sensors that are frequentlyused for positioning determination based on dead reckoning in robotics.

In theory the distance can be obtained if the linear acceleration, that is measured from an accelerometer,is integrated with time. It seems simple, but it can be difficult to realize. An accelerometer is not able todistinguish between actual acceleration of the sensor and the earths gravity, and with 3 axis the gravity gwill be distributed over those axes depending of the orientation of the sensor. Therefor to get rid of the gcomponent the orientation has to be known with accurate precision. This can be done with the aid of a threeaxis gyro. With the orientation acquired from the gyro it is possible to calculate the gravity contributionto each axis of the accelerometer, and with simple subtraction of that contribution the accelerometer be-comes independent of g. It is a simple way of thinking, but there is quite heavy math behind those equations.

The angular velocity data from the gyro can be used to calculate the quaternion q, which then is used tocalculate the g’s contribution to the acceleration of each axis. Quaternions are well known in mathematicssince the 19th century. How it can be used to compute direction is shown in equation 1,

g =

2 ∗ (q(2) ∗ q(4)− q(1) ∗ q(3))

2 ∗ (q(1) ∗ q(2) + q(3) ∗ q(4))

q(1)2 − q(2)2 − q(3)2 + q(4)2

(1)

where the vector g is gravity at each axis. Equation 2 shows a simple subtraction of the g to the rawacceleration data in vector a. The A is the resulting acceleration without the contribution of the gravity.

A = a− g (2)

A potential problem is the measurement inaccuracy which is a reality. A small error in the gyro wouldgive an even bigger error in the accelerometer data. This statement is strengthen by Table 2 where equation1 and 2 is used to calculate what an error in angle affects the position.

2.4 Time

Even though time is relative, it is reliable in normal circumstances and can be used to determine the distancebetween two units. The units can be communicating with e.g. RF or ultra sound. Measurements based ontime is practically AoA but can be performed in different ways. Time of Arrival (TOA) is one such wayand synced clocks is another. Devices based on ultra sound usually measure the time for a sent signal to bereflected and return from target, then simply convert that measurement to a distance, which is easy since

5

those two parameters are linear. Radar works in a similar way, but with the difference that more signalprocessing can be done to increase the accuracy of the measurements.

6

3 Positioning Techniques

When measurements are acquired the positioning is required. The positioning techniques are based on andlimited by the measurements in many ways. Some common positioning techniques for wireless RF-based IPSsare covered and discussed in this section. To improve the position, algorithms can be used to handle smallerrors in measurements, or involve history for a more probabilistic position. Also some different networktopologies for wireless systems will be discussed.

3.1 Topologies

A wireless network can be structured in different topologies, and the different nodes can have differentproperties, which allows the designer to create a customized system. There are basically two categories ofnetwork topologies: physical topologies and logical topologies. The physical refers to the cabling layout,the location of the nodes, and the interconnections between the nodes and the cabling. The logical refersto the structure of the signals interaction in the network, and describes the way that the data travels be-tween nodes. The logical topology generally follow the same topology as the physical topology of the network.

A topology can be created with three different nodes: end devices, routers and coordinators. A coordina-tor is a device that relay messages in the network. It is the principal controller of a Personal Area Network(PAN), and therefor there can only exist one coordinator in a network. The router acts as a coordinator, itforward messages from one node to another, but is not the primary controller in the network. A router canalso take the role of an end device. An end device has fewest processing capabilities and features. It canonly communicate with its parent, which can be either a coordinator or a router.

There are eight basic topologies [30]: star, mesh, tree, point-to-point, bus, ring or circular, hybrid, anddaisy chain. Only the three first will be covered, for those are the most common when creating an IPS.

• In a star network, illustrated in Figure 1a, each node is connected to a central node with point-to-pointconnections. Communication is allowed only between the central node and the peripherals.

• In a tree network, illustrated in Figure 1b, the devices have a parent-child relationship. The structureis composed of a root node, intermediate nodes, and leaves. The root node is the main node, the leavesare the last nodes, and the intermediate nodes are the nodes in between the root node and the leaves.The leaves acts as child nodes to the intermediate node, just as the intermediate nodes are child nodesto the root node. Each node in the network can only communicate with its mother node or child node.

• In a mesh topology (Figure 1c), each device can communicate directly with any other device, if thedevices are close enough to establish a successfull connection. All nodes can participate in relayingmessages resulting in all messages reaches the final destination in the network in fastest possible way.The advantages and disadvantages of mesh can be sumarized as follows:

Advantages

– Every node can forward the information, and therefore the range of the whole network increases.

– Because every node forward the information, the range of a single end device does not have to belarge, which is energy-saving.

– Because of the topology, there are many different ways for the signal to take. This means that ifone node breaks, there is almost always another way for the packages to take.

– The package always reaches its destination in the shortest way.

Disadvantages

– The layout of a mesh topology is expensive to implement. But once implemented, the meshtopology can pay off with time.

7

– The response time increases, because the packages often has to travel by several nodes instead ofdirect to the correct device.

(a) A star net-work (b) A tree network (c) A mesh network

Figure 1: Typical network topologies for ZigBee

A wireless network can be structured in three different topologies used for positioning: network-based,terminal-based and terminal-assisted [7]. The different positioning topologies are graphically shown in Figure2a, 2b and 2c.

• Network-based topology consists of several Access Point (AP)s that receive broadcasts from a mobiledevice. The information is then redirected to a central server, where the calculations are performed.This topology requires that the positions of all stations are known, unless fingerprinting (covered inSection 3.3) is used. A valuable advantage is that the mobile device e.g. smart phones, does not needany additional hardware.

• Terminal-based topology has the exact opposite function than the network-based approach. The mo-bile device receives information from several APs and performs the calculations. The mobile device canactively send out requests and wait for the APs to reply with information, or it can wait for broadcastsfrom the APs without asking for it. Those modes are called active respectively passive terminal-basedtopology.

• The Terminal-assisted approach is a mix of network-based and terminal-based topologies. The mobiledevice receives data from APs and redirects the information to a central server, where calculations aremade.

3.2 Location estimation algorithms

This section will cover some useful algorithms which are often used when creating an IPS. Location deter-mination would be an easily solved problem, and would be solved with trigonometry or a relatively simplealgorithm. But because of the inaccuracy in RSSI and because of that the relationship between RSSI anddistance is not straightforward, the location estimation often requires a more complex positioning algorithm.The algorithm can be relatively simple but yet result in a relatively good estimation of the position.

Min-MaxThe Min-Max algorithm is one of the simplest algorithm to implement when create a system for localization.The algorithm uses incoming RSSI values from several beacons and calculates estimated distances from eachbeacon. The algorithm places a squared box around each beacon, see Figure 3. The estimated distances for

8

Mobile device

APAP AP

Central server

(a) Network-based positioningtopology

AP AP AP

Mobile device

(b) Terminal-based positioningtopology

AP AP AP

Mobile device

Central server

(c) Terminal-assisted positioningtopology

Figure 2: Different positioning topologies

the beacons is multiplied with two and set as the length of the box. The intersection of those boxes indicatethe position of the mobile device. The estimated position is assumed to be in the middle of this box ofintersection.

Figure 3: Determining position using Min-Max

MultilaterationMultilateration is an algorithm based on the properties of geometry. The system uses RSSI values for distanceestimation between beacons and the mobile device, and the algorithm creates circles having the euclideandistance as radius around each beacon. In an ideal case the intersection of the circles identifies the positionof the mobile device, but often there are errors in the distance measurements which does not result in asingle intersection. If the area in where the position of the mobile device are to be determined is subdividedinto small cells of finite size, the algorithm can calculate the sum of the squared distance between the celland each circle. The position of the mobile device are then assumed to be in the center of the cell in wherethe sum is lowest.

9

Least SquaresLeast Squares (LS) method focuses on minimizing the value of the least square objective function, equation3. (x, y) is the position of the mobile device that is to be determined, (xi, yi) is the coordinate of the i-thbeacon and ri is the range measurement to respectively beacon. N is the total number of beacons.

[xLS , yLS ] = argminx,y

N∑

i=1

(√

(x− xi)2 + (y − yi)2 − ri)2 (3)

ROCRSSIThe general idea of the ROCRSSI (Ring Overlapping based on Comparison of Received Signal StrengthIndicator) algorithm is to create a series of circles around each beacon, see Figure 4a, from which the mobiledevice takes advantage of when estimate its position. The circles can be generated before or during thepositioning phase. If generated before, measurements of RSSI on different distances from each beacons hasto be done. The circles can also be generated at the same time as the positioning is to be determined, ifeach beacon receives RSSI from another beacon.

The algorithm uses the circles to narrow down the possible area in which the estimated position is to bedetermined. If the distance between A and the mobile device M is larger than the distance between the Aand B, but smaller than the distance between A and C, it can be assumed that the mobile device is withinthose two circles that the distances B and C creates around the beacon. This is illustrated in figure 4a. Ifone or more beacons are registered to be in range of the mobile device, the position of the mobile device isestimated to be in the intersection of the areas created from the circles.

Circles can be created if the beacons receive RSSI from other beacons. In Figure 4b, A, B and C arebeacons and M is a mobile device. Let us call RSSIAM as the RSSI from a message that is transmitted fromA to M, and so on. If RSSIAB < RSSIAM < RSSIAC and RSSIBA < RSSIBM < RSSIBC , then M canbe assumed to be in the shadowed area. ROCRSSI assumes that the system uses omni-directional antennas.

(a) ROCRSSI with known distances B and C from beaconA (b) Example of ROCRSSI

Figure 4: Function of ROCRSSI algorithm

Maximum LikelihoodThe Maximum Likelihood (ML) algorithm is a method of estimating parameters of a statistical model,and is in positioning based on interference. Collected RSSI values from n beacons are stored in a vec-tor, ρ = ρ1, ρ2, ..., ρn along with coordinates of respectively beacon, xb = xB,1, xB,2, ..., xB,n andyb = yB,1, yB,2, ..., yB,n. For each possible position of the mobile device, the algorithm computes a prior

10

probability of receiving ρ. The position with the highest probability is assumed to be the estimated position.

3.3 Fingerprinting

Fingerprinting is as a method where the signal strength for different positions in a room are measured andstored. Data for a specific point is called a fingerprint. The technique can in most cases be implementedby software, without any additional hardware. This makes fingerprinting a cost effective and less complexmethod compared to other techniques for IPSs. Another advantage with the fingerprinting method is thatno time synchronization between the stations is needed.

Fingerprinting typically consists of two phases: offline training, also called calibration-phase, and onlinepositioning determination.

In the first phase, data is gathered. Fingerprints, containing information about all fixed stations and theirRSSI is taken at a number of points in the area in where the positioning should later run. The fingerprintoften comprises numerous measurements taken over a certain time, often several minutes, to get the averageRSSI in that point. The fingerprint is often represented in form of a vector, containing the average signalstrength and the position. The size of the vector depends on the number of APs that are available at thatspecific position. All the gathered fingerprints are stored in a database, called a radio map. An example ofhow the signal strength spreads from APs are shown in Figure 5.

Figure 5: Example of signal strength from APs

Phase two is the actual position determination phase. The mobile device that should be located in the

11

recorded area measure the RSSI of all the current stations in range, and stores the data in a vector. Thisvector is then compared to the vectors in the radio map, and the closest match represents the position ofthe mobile device.

Because the quality of the RSSI is dependent on Line of Sight (LOS), changing the environment cancompletely destroy the radio map. Introducing small ordinary objects in a room such as an extra chair willnot affect the radio map considerably. However, placing an object of metal close to an AP can be devastatingfor the radio map. To improve this, information about the direction can be added to every fingerprint. Thecalibration-phase takes longer time, but the result in the second phase improves. Using fingerprinting as amethod when constructing an IPS can generate meter-accuracy, but this depends on the density of the APsand the fingerprints.

3.4 Trilateration

Trilateration is a method to determine the relative position of points by using measured distances andgeometry of circles or triangles. In a three dimensional case spheres will be used instead of circles. Since itis a simple and very straight forward method to locate a point relative other points, trilateration is widelyused in Real Time Locating System (RTLS). Global Positioning System (GPS) are one of the most knownsystems using 3D trilateration to determine the position of devices [4]. A simple two dimensional illustrationis shown in Figure 6 where there are three stationary points P1-P3, and three mobile devices m1-m3 whoseposition needs to be determined.

Figure 6: Trilateration

Each of the stationary point has a maximum range of where mobile devices can detect the signal, rep-resented as a circle with the stationary point in origin. If a mobile device m3, discover only one stationarypoint as illustrated in the figure, the position cannot be determined more accurately than somewhere on theradius of the Euclidian distance between P1 and m3 around P1. As seen in the figure, m1 is in the range ofboth P1 and P3, which will narrow down the possible locations to two. For the case where a mobile devicem2, is in range of three or more stationary points the possible position can be only one. This is normaly

12

true for both the 3D and the 2D cases. The position is only determined relative the stationary points, butan absolute position can easily be determined if the positions of the stationary points are known.

For an ideal case, where the distance is measured without error, the position can be determined exactly.But reality is rarely so, and therefore the position will almost always have an error, even if it is small. Thebig problems occur when the error is too large for satisfaction. The solutions are many, but with trilaterationthere is one simple way; introduce additional stationary points. The standard deviation can be reduced byadding more stationary points to the system, which will result in a more accurate location estimation.

3.5 Multilateration

Multilateration is a technique similar to trilateration in the way that both use distance for estimating theposition. It is the measurements that makes the techniques different from each other. Trilateration uses theEuclidean distance between a stationary point and a mobile device while multilateration uses the differencein distance from a mobile device to two different stationary points. When using RF communication, TDOAis commonly used as measurement technique instead of distance difference. Since only the difference indistance is measured and not the actual distance, the two stationary points will not give a finite number ofpossible locations. The pattern of possible solutions can be realized as a hyperbolic curve. Because of this,multilateration is also called hyperbolic navigation. Three hyperboloids intersecting are needed to determinethe location in 3D, i.e. at least four points are needed to get the 3D location. More than four will decreasethe error which occurs in a realistic environment.

Figure 7: Multilateration

Multilateration is mostly used to locate nearby airplanes by Secondary Surveillance Radar (SSR). Asimple illustration in 2D is shown in Figure 7 with three stationary points and one aircraft representing thelocation to be determined. The hyperbolas represent the possible locations of the aircraft for each pair ofpoints, and together the intersection is the resulting estimation of the position.

3.6 Triangulation

Triangulation estimates the location with the use of geometrical properties of triangles. The exact positionof a mobile device, m1, can be calculated if the positions of two base stations and respectively angle (A1 andA2) between the base stations and the mobile device are known, see Figure 8. The incident angle can beobtained by AoA measurements. Assuming the coordinates of the two base stations are known, meaning thatalso the length between them is known. When one length and two angles of a triangle are known parameters,the lengths of the other two sides in the triangle can be calculated. This means that the position of themobile device can be obtained.

13

Figure 8: Triangulation

Triangulation can be deceptive in no LoS conditions, therefor at least two independent triangulationdeterminations should be made to confirm the position of the mobile device.

3.7 Cell of Origin

Cell of Origin (CoO) is an inaccurate but simple method for positioning. The access point generating thestrongest RSSI value is identified and the position of the mobile device is assumed to be close to that accesspoint. The shapes of the cells that the net is constructed by can be approximated to for example squares,triangles or circles, and an usual apporximation is hexagons, see Figure 9.

The accuracy of CoO is related to the density of access points. Because of the sometimes relativelylow accuracy, CoO is often used in conjunction with some other technology, such as TOA, when precisionis important. Although CoO is not as precise as other methods, it has unique advantages. It can quicklyidentify the location, and it does not involve any complex location-tracking algorithm.

14

Figure 9: Structure of Cell of Origin

15

4 Technologies

ARTLS require some hardware/technology to perform the measurements. The choice of technology/technologiesis one of the most important choice, together with measurement technology which are in a way interdepen-dent. Note that all measurement techniques are not applicable with all technologies.

Most of the technologies are based on wireless signals, but the increasing popularity of RTLS has resultedin alternative technologies to be examined. The most frequently used are investigated in this section.

4.1 Bluetooth

Bluetooth is a standard that was developed by Ericsson as a wireless replacement to RS-232 cable. It oper-ates in the unlicensed ISM band between 2.4-2.485 GHz. Today it is used to connect headsets, keyboards,laptops, cell phones and other electronical devices. The maximum range is 1-100 meter depending on howthe transceiver is designed.

Bluetooth can be subdivided into three different classes, see Table 3. Typical implementations for class 1is industrial use and devices without power limit. Class 2 and 3 are often used in battery charged implemen-tations. The maximum ranges in the table depends on the conditions, such as LOS, antenna configurationand material coverage.

Table 3: Maximum ranges and output power of different classes

Class Maximum range Maximum output powerClass 1 100m 100mWClass 2 10m 2.5mWClass 3 1m 1mW

Bluetooth uses a radio technology called frequency-hopping spread spectrum, which means that the fre-quency is switched in a random but predictable sequence during the transmission. The frequency switches1600 times per second, and this technique reduces interference and shortening the transmission delay. Blue-tooth use the same frequency band as WiFi, but because the use of frequency-hopping the two technologiescan operates simultaneously.

Bluetooth is subdivided into different profiles. Each profile defines possible applications, specifies generalbehaviors and includes settings to parametrize and control the communication between Bluetooth devices.Some of the advantages of Bluetooth technique is that it is cheap, has low power consumption and up to255 devices can be connected together in the same Local Area Network (LAN).

BLE was introduced in 2011, and was specified as Bluetooth v4.0. BLE works like classic Bluetooth,but have different characteristics and new features; among others, and maybe the most important, it hasextremely low power consumption. It consumes between 1/2 and 1/100 the power of classic Bluetooth tech-nology. BLE transmit short bursts of data instead of a continuous stream which classic Bluetooth do, andthis is why BLE is so low-power consuming.

There are two types of BLE devices: single and dual mode. The single mode only supports BLE protocol,while the dual mode supports both BLE and classic bluetooth. The dual mode stack has two independentprotocol, which share common RF blocks.

Positioning with Bluetooth is one of the more proven technology. It can be subdivided into two parts:positioning using already existing devices and protocols, and positioning with the use of modified devices.The positioning methods are limited with the use of existing devices, only proximity and RSSI-based methodscan be used, and the accuracy is not that high as with the use of modified devices. It is relatively simple toconstruct an IPS with the use of a proximity method. The only needs are Bluetooth devices, an application

16

and a database containing the positions of the fixed Bluetooth devices. To increase the accuracy of an IPSbased on proximity methods, there can be more devices added to the system.

The authors in [5] have designed and implemented an IPS that is based on RSSI measurements. Thesystem achieves an accuracy of 3.76 meter. Because the system also is based on measurements of the receivedpower level, the accuracy of the system would increase if the Bluetooth devices are able to measure RSSImore precisely.

The company SenionLab [25] has developed an IPS based on fusion of data from motion sensors, WiFiand BLE. The system uses fingerprinting as positioning technique, and reaches an accuracy of 1-5 meter.

4.2 WLAN

The modern Wireless Local Area Network (WLAN) is called Wi-Fi, which is a network infrastructure basedon IEEE 802.11 standards and operates in the 2.4, 3.6, 5 and 60 GHz frequency bands. IEEE 802.11 issubdivided into a couple of sub-standards with different properties.

A WLAN often consist of one or several APs and one or several clients that are connected to the APs.The clients can for example be PCs, mobile phones or other things that supports WLAN. The connectionsare based on Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) for path sharing, which is aprotocol for carrier transmission in 802.11 networks. In CSMA/CA the node which is about to send datachecks if the common channel is clear before the package is sent. If the channel currently is occupied byanother node transmitting data, the node that is about to send will wait a randomly chosen period, andthen check again if the channel is free.

Because of the popularity to use WLAN to offload the mobile networks, it can be found in almostevery building nowadays. An IPS built on WLAN is easy to create when no extra specialized equipmentis required. Another advantage is that it executes signal scanning quickly, and LOS is not necessary. Therange is also good compared to other technical solutions, 50-100 meters and sometimes up to 150 meters.Although the range is good, using WLAN to create an IPS result in low positioning accuracy. The accuracyis approximately 3 to 30 meter according to [9]. To compensate and improve, in addition to increase thenumber of APs, complex positioning estimation is needed. The high energy consumption which followswith WLAN will lower the lifetime of any battery based device. An IPS based on WLAN is also highlyinfrastructure dependent [8]. The most common measurement method in WLAN based IPS is RSSI sinceany other requires hardware modifications.

4.3 Radar

Radar is an acronym for Radio Detection and Ranging, and was developed to detect objects with RF signals.Radar can not only detect objects but also determine the position and velocity of the object. When the radiowaves from the transmitting radar encounter a moving object the reflecting waves will have a slight changeof frequency which can be explained by the Doppler Effect. The returning power of the wave are affected byparameters mentioned in the list of symbols below. Equation 4 shows the relationship to received power.

Pr =PtGtArσF

4

(4π)2R4(4)

Range detection by radar gives high accuracy for the possible ranges, but heavy signal processing isrequired which makes radar a complicated option for an IPS. A radar system can use pulses to determine therange to an object. another alternative is to use a Continuous-Wave (CW) which consist of a single stablefrequency and is effective when determining speed. A Frequency-Modulated Continuous-Wave (FMCW) onthe other hand can provide both range and speed accurately. Both those two types of radar can be used to

17

List of symbols

Pr Received powerPt Transmitted powerGt Gain of transmitting antennaAr Effective aperture (area) of the receiver antennaσ radar cross section (measurement of how detectable the object are)F Pattern propagation factorR Distance from transmitter to targeted object

design a RTLS. This is done by the authors in [11].

An idea to use cognitive radar is formed by [12] which essentially means that the radar is learning by itsenvironment, and has the possibility to act based on those experiences. The advantages of using radar forthe construction of an IPS are probably too few to compensate for the drawbacks, but that depends on theapplication.

4.4 ZigBee

ZigBee is a wireless technology developed to connect and control several different devices. It can be usedfor everything from home appliance to applications in industries. The IEEE 802.15.4 standard protocolwas created and ratified by the ZigBee Alliance [13] and IEEE [14]. It has low data transmission, and is acost-effective and energy-efficient technique.

ZigBee is developed and adapted for Machine to Machine (M2M) communication, which means that thedevices can communicate without a device that coordinates the communication between them. A devicethat can coordinate communication is only needed if the network is supposed be connected to internet or toa network that operates in another technology. A huge advantage that overcomes most other technologies isthat ZigBee in theory supports more than 65 000 devices in the same network [15].

According to the protocol there are two different hardware nodes that can be used to create a network:Full Function Devices (FFDs) and Reduced Function Devices (RFDs). A FFD is capable of performing allthe tasks in the IEEE 802.15.4 protocol, and can therefore accept any role in the network and can communi-cate with any other device in the network. A RFD has limited capabilities, and can only communicate witha FFD device. Because of the limitations of a RFD, the processing power and memory size are normally lessthan of a FFD.

ZigBee uses three different type of software defined nodes: coordinator, router and end device. Those areearlier discussed in section 3.1. The protocol allows the devices to communicate in three different networktopologies: star, tree and mesh (discussed in section 3.1). The mesh topology is the most common topologyfor ZigBee networks.

4.5 GNSS

GNSS, Global Navigation Satellite System, is a worldwide navigation system. The most known is GPS,but the Russian GLONASS and the future European Galileo are two other GNSS systems. The systemsuse satellites and pseudo-satellites (local ground based transceivers that operates commonly to satellites) tonavigate via trilateration.

Originally the system was used in the military, but these days it is used by civilians to navigate outdoors.Almost every new cellphone is equipped with GPS. Because the system need line-of-sight, it does not workinside buildings. The receiver requires a minimum number of four satellites to calculate the position, butoften there are more satellites available which increases the accuracy. The accuracy can then become around

18

a few meters.

An IPS can be build based on pseudo-satellites, also called pseudolites. One advantage is that the systemcan be based on similar hardware to GPS. The system is therefore compatible with GPS, which means thatonly one receiver is necessary when switching between outdoor and indoor environment. This also impliesthat the size of the receiver decreases. Another advantage is that GPS receivers are relatively inexpensivesince a huge number are produced. There are of course some disadvantages with the use of pseudolites whenconstructing an IPS: the near-far problem, which means that when a receiver is close to a pseudolite thepower of the signal from that pseudolite is so strong that the receiver has trouble detecting signals fromother pseudolites. Also interference and the dependence of LOS is a problem, and the integer ambiguityresolution has to be resolved [16]. Integer ambiguity is a value of the length between the satellite and thereceiver expressed in number of wavelength. Carrier-phase measurement is a measure of the integer ambi-guity, and can be done in two solutions: either the pseudolite or the receiver has to keep moving, or dualfrequency has to be used. Because of those problems, pseudolites are not so common when constructing IPSs.

Locata Corporation has developed the GPS-based IPS named Locata [21]. The system uses pseudolitesand reaches an accuracy at cm-level.

4.6 RFID

Radio-frequency Identification (RFID) is not a new technology, even though it has become well known inrecent years. The RFID standard have spawned a similar standard named Near Field Communication (NFC)which has expanded so much that newer smart phones are equipped with a chip or a so called ”tag”. NFC iswell suited for access cards and small amount payments because of the very short range of less than 2 dm, andtherefore it is hard to pick up the signal. A passive RFID tag is powered by the electromagnetic field fromthe transceiver that it is communicating with, which makes the tag literally powerless when taking away thereader which it is communicating with. An active tag is on the other hand powered by a battery or anotherexternal power source, which has its own advantages and disadvantages depending on implementation.

RFID is used in many cases to create RTLSs because of the inexpensive deployment of such systems andbecause of that such a system can handle large quantities of tags. An active RFID tag can be read on dis-tances of 100m with accuracy under one meter, which makes RFID RTLS quite usefull in some applications.

SpotON [22] is a three dimentional location system based on RFID and received signal strength analysis.The system reaches an accuracy of 1 m.

4.7 Camera

An ordinary camera all by itself is quite useless as an IPS, but the remarkable progress in computer visioncan change such statements. A 3D camera combined with computer vision can be used to create a 3D mapof the surroundings, which is used to calculate its position. When Microsoft in 2011 released a softwaredevelopment kit (SDK) for their Kinect, computer vision began to advance rapidly and still is.

There are more ways than using camera mapping to set up an IPS based on cameras. A 2D camera canwith the use of Visible Light Communication (VLC) act as an receiver for a Light-emitting diode (LED)that transmitt signals with such a frequency human eyes are undisturbed. Then by mounting lots of LEDsin the roof, each with an uniqe frequency, and use a camera as receiver, an IPS can be constructed. Thecamera could advantageously be a smart phone which has the possibility to make it easy and cheap for auser. Such systems are not cheap but has the possibility to be very accurate.

The author of [17] uses a device to measure Optical Angle of Arrival (OAoA) which results in an meanerror of 1.69 cm.

19

4.8 Ultrasound

Ultrasound can be used for many purposes such as in medical and science, but only ranging and detectionwill be explained in this section. The frequencies used for ranging and detection usually span between 20kHz to 40 kHz, which the human ear can not detect. An IPS based on ultrasound beacons needs a parallelsystem, since ultrasound lack the ability of communication. A system based on sound waves could be prefer-able in some cases where electromagnetic fields should be avoided such as airplane cabins or close to sensitivemedical equipment. Because of slow propagation in air TDOA is a preferred choice of measurement technique.

The authors of [10] have constructed a system of ultrasound receivers for measurements and connectednodes to a ZigBee network for communication. The sensor data is sent back to the ultrasound transmitterwhere a computer perform the position calculations. With such simple system a root mean square error of2 mm is achieved.

It is preferable in most cases to have a system that is compatible with modern smartphones. Themicrophone in a smartphone have the capability to record not only acoustics, but also ultrasound. Thismeans that a smartphone in theory are able to act as receiver in an ultrasound RTLS.

4.9 GSM/UMTS/LTE

Global System for Mobile Communications (GSM) is a standard describing the protocols for the second gen-eration (2G) digital cellular networks used by mobile phones. It is developed by ETSI, European Telecom-munications Standards Institute. It is a global standard and is used in over 219 countries and territories,and by more than 6 billion people [18]. GSM is as mentioned a cellular network, which means that the areain which it operates are subdivided into cells, in which each cell is served by at least one fixed-location basestation. Each cell uses different frequencies than its neighboring cells. This avoids interference and providesguaranteed bandwidth within each cell. The shapes of the cells are often hexagonal, but can be squares,circulars or some other regular shape. Each cell in a GSM network has a size up to 35 km.

GSM-based IPSs have several advantages. It has good coverage, it is accepted by every cell phone whichmeans that no extra hardware is needed, it operates in a licensed frequency band which decreases the in-terference, and the channel to cell allocation is a complex and costly process. Its complex process mightbe seen as a weakness for the system, but in fact it results in a stable network that can operate for a longperiod before having to be recalibrated.

According to the authors in [19], their GSM based IPS reaches an accuracy of five meters indoor in alarge multi-floor building. The system is based on fingerprinting.

Universal Mobile Telecommunications System (UMTS) is the third generation (3G) wireless standardsand it is based on GSM. UMTS can not use the same base stations as GSM. However, UTMS operates ina common core network that supports multiple radio-access networks, including among others GSM. Thisnetwork is called the UTMS multi-radio network.

Long-Term Evolution (LTE) is based on GSM and UMTS, and is also called 3.9G. LTE is the generationafter UMTS, and does not fulfill all the standards for LTE-advanced (4G), therefor it is known as 3.9G. Thefirst publicly available LTE was set up in Stockholm and Oslo in 2009, and it is now widespread globally. Inthe same way that UMTS coexists with GSM, LTE coexist with UMTS and also GSM.

A LTE-based IPS was constructed by a team in South Carolina [20], and the system reaches an accuracyof less than 6 meters. The system is based on TDOA.

20

5 Summarization of already existing systems

From all the techniques and technologies already discussed it is understandable that not all techniquescan be combined with all technologies. Todays situations often require handmade solutions, where differenttechnologies are suitable for different applications. Often the systems are hybrids of two or more technologiesor composed by two or more technologies working in parallel. Table 4 includes a summary of some existingsystems on todays market.

Table 4: Summary of some specifications for different technologies

System Technology/Technique Positioning Algorithm Accuracy

Bluetooth Lo-cal PositioningApplication [5]

Bluetooth, RSSI Propagation model,Kalman filter

3.76m

RADAR [11] WLAN, RSS kNN, Viterbi-like 2-3m

TELIAMADE [10] Ultrasound, ZigBee, time-of-flight, multilateration

Least squares method 2mm

GSM-based indoorlocalization system[19]

GSM, Fingerprinting kNN 5m

SenionLab [25] Wifi, BLE, Fingerprinting NA 1-5m

HAIP [24] WLAN, BLE, Angular esti-mation

NA 0.3-1m

Particle filter based[20]

LTE, TDOA Particle filter 5.35m

LOCATA [21] GPS/GNSS EKF (Extended KalmanFilter)

20 cm

SpotON [22] RFID, Signal Strength Aggregation 1m

LANDMARC [23] RFID kNN 2m

TeleTracking [26] IR, Ultrasound, RSSI, tri-angulation

NA Several me-ters

According to those comparisons, it is unusual that an IPS achieves an accuracy of better than 1 meter.The most frequently used technologies are WiFi and BLE, and the better performing systems are based onseveral technologies.

21

Part II

ZBeacon

6 Indoor Position System

This section will contain details about our own implementation of an IPS. The background will describe thecase and conditions for the system while solution will be the actual design and how the problem were solved.The Results contains measurements and tests showing that the system actually works.

6.1 Background

When people go shopping at the supermarket, they sometimes buy a lot of food. In large supermarketspeople can struggle with finding all items on the shopping list, and it takes time. An IPS can be used tofacilitate and optimize peoples shopping routines, and especially: reduce the time for the customers beingin the store. The system can for example be implemented as an application for smart phones, where theuser add items before entering or when arriving to the supermarket. The application sort the items andcalculate the best way to pick up all products. The users can see on their screens in which direction togo for finding the next item. As described so far, no supermarket would want such a system. This isbecause a lot of spontaneously shopping would be avoided when all user concentrates on the directions onthe screen. Therefore an advertisement system could be implemented for the supermarkets special prices,and pop up message noticing the user about it when passing by particular products. If the customer wantto add things on the list, the system recalculates the route. The possibilities are endless for both customerand supermarket.

An IPS implemented in a supermarket only require the accuracy of a few meters, but enough for the userto know for a certainty between which shelfs the user are positioned.

With regard to all the knowledge gained and presented in Part I we chose to implement and investigatea RF solution with a fairly simple positioning algorithm to begin with. The most suitable RF equipment forthis were either BLE or ZigBee which both have their pros and cons. The main advantage of BLE is that italready exist in mobile phones and tablets which makes it easy to utilize a customer’s own hardware whichin turn could reduce the cost of the system. The drawback of BLE is the network structure, which is one ofthe strengths of ZigBee. The ability to communicate with all nodes and beacons in a system could be veryuseful when nodes have to be reconfigured or monitored. It could also provide information about when it istime to change battery in certain nodes or if any nodes are broken or malfunctioning. Both ZigBee and BLEare very energy efficient, even though BLE is slightly more efficient. Since ZigBee were most convenient forus the decision to use ZigBee were made. We acquired devices from the company Wiotech [27] which focuson development of ZigBee WSN.

6.2 Solution

The measurement technique that was decided to be used is based on RSSI since it is simple and no hardwaremodifications are needed. The RSSI values are processed and used as the input for calculations via trilater-ation and together with a simple algorithm an estimated position is calculated.

The beacons and mobile devices were designed to fit the terminal-based positioning topology in Figure2b, with the modifications shown in Figure 10. The reason network-based positioning topology is not usedis because the connectivity from the AP’s to the central server would result in a lot more wireless data, andtherefor more interference. It is also a mater of energy savings, since AP’s would have to be routers, whichin turn require external power source or repeatedly battery replacement. The AP’s in the terminal-basedtopology is comprised of end devices, which are beacons for the reason that power consumption of the sys-tem should be as low as possible. The beacons will be able to be powered by batteries and therefore makethe deployment and maintenance simpler. The terminal-assisted positioning topology is not suitable either

22

APAP AP

Computer Accelerometer SmartRF05

Figure 10: Topology of ZBeacon system

because the information is requested by the mobile device and not by a central server. If the estimation ofthe position can be done on board of the mobile device it is preferable, since it avoids the need of an extraunit. The mobile device comprise of a computer interfaced with a Zigbee router and a mobile phone fromwhere accelerometer data are given.

The ZigBee chip on the devices are CC2531 created by Texas Instruments [28], TI. The program IAREmbedded Workbench IDE (integrated development environment) from the company IAR Systems [29] isused to program and debug the devices. The software is based on TI’s Z-stack which comes with the CC2531chip. The system comprise of end devices that frequently sends out an ID number specific for that beacon.The mobile devices in the system is programmed as routers, which receives data from the end devices ifin range. There is also a coordinator in the network, which initiate the network and invite routers. Bothcoordinator and routers has the property to receive data from the end devices. A router when initiated hasthe permission to initiate other routers and end devices, which means that the network does not need thecoordinator more than to initiate the network.

The end devices are programmed to frequently (every 100ms) send out a for each device individual IDnumber. When a router or coordinator is in range of an end device it receives data from that end device,included among others the ID of the end device. The RSSI is provided by the radio module for each packagereceived. When a ZigBee device transmits a message, the z-stack automatically add data required by theprotocol before transmitting over the air. The ID and the newly acquired RSSI of the signal is composedinto a new package which is transmitted serial via UART to a computer.

When measurement data are collected by the devices and received to the computer and MATLAB, theRSSI values in dBm is converted to distances in meter. The conversion is done by firstly determine the pathloss exponent n through equation 5 [6]. The propagation constant is often assumed to be 4 indoors, but thatis very dependent on the environment since indoor is a very general expression. An improving operation toget a more accurate position is to calibrate each node separately, to get an individual path loss exponent foreach node. If not calibrated for each node the estimated distance will definitely vary depending greatly onits close environment.

n = −RSSI −A

10log10(d)(5)

In equation 5, A is the RSSI value for 1m distance and RSSI is the measured RSSI at distance d. Theestimated distance can be calculated with equation 6 which is derived from equation 5.

d = 10−RSSI+A

10n (6)

23

The mobile device has to be in range of three as a minimum number of end devices to be able to calculatea position of the device. When in range of three or more end devices, the estimated distances are processedwith different filters to achieve a better accuracy of the position.

The map in which the position is graphically displayed is manually created in MATLAB from a digitalimage. The positions of the beacons are manually included and stored in an array in MATLAB.

24

6.3 System Verification

This section will describe how tests were done to verify the function of the system. It is important to executetests to detect the performance of the system. The tests are divided into two groups: tests of the devicesperformed independently of the system and tests of the performance of the system.

6.3.1 Device tests

The tests described in this subsection are performance tests of the devices. Those tests had to be done partlyto get to know the devices, and partly to achieve different parameters that are to be used in the designingof the system. But the most important factor of why tests of individual devices had to be done was to proveand validate the idea that an IPS can be based on RSSI measurements.

Distance tests outdoors at a fieldDistance tests on a field far from disturbances and interferences were done to validate that the devices canbe used to create an IPS. Two devices were tested, one with the function of a transmitter and one with thefunction of a receiver. Respective device was attached to a stick with the length of 1 meter above ground,faced vertically towards each other.

The transmitter is able to use 16 different output power between -28 and 4.5 dBm [31]. The transmitteris programmed to send out 100 packages with each output power, resulting in a total of 1600 packages. Apackage is sent every 100 ms. The transmitted message is a six byte long package, including the packagenumber and the output power. The receiver obtains the RSSI of the message and generates a new messageof nine bytes: package number, RSSI and output power. The package is thereafter sent to the computerwhere it is stored for future calculations. The configuration for the distance tests can be seen in Figure 11.Measurements was taken for every meter between 1 and 10 and at every 10 meters upp to 100m. Resultsare shown in Table 5 and Figure 13 for measurements up to 10m, and Figure 14 for measurements up to100m in section 6.4. Additional measurements were taken at a distance of one meter, when the RSSI ofthose measurements was to be used in future calculation.

Figure 11: Configuration for distance testing outdoors

Rotating receiverThis test was done to evaluate how the arrival angle at the receiver device affect the RSSI, i.e. the directivityof the receiver. Three beacons and one receiver were placed outside on a big field far away from disturbances.Figure 12 shows the configuration. The beacons sent out a package containing an individual ID number every100 ms. The receiver receives data from all three beacons, which it transmits to the computer where it isplotted graphically. Both a device from Wiotech and a evaluation board from TI were used as receivers. The

25

result is presented in Figure 15 and Figure 16 in section 6.4.

Figure 12: Configuration for rotating receiver test

Test for antenna at transmitterA similar test that the ones just described was done for the transmitter, to detect the directivity of thebeacon. A transmitter was placed in an wide open area far from metallic objects, programmed to send dataevery 100 ms. The receiver was rotated around the transmitter, at a constant euclidean distance and withthe same side constantly faced towards the transmitter, in a half circle of 180 degrees. Result is shown inFigure 17 in section 6.4.

Accelerometer testThe dead reckoning measurements produced by the accelerometer is investigated in accuracy and how

large errors that can be expected. The device was placed on a flat steady surface, for accuracy and standarddeviation measurements. When moving the device along the x-axis the resulting linearly integrated distanceand velocity are shown in Figure 18.

6.3.2 System tests

The tests described underneath are for the system in whole, and will serve as the basis for the descriptionof the accuracy of the system. It is important to perform thoughtful and proper tests of the system, inadvantage to achieve truthful and reliable results for descriptions of the accuracy.

Move along a predefined routeTo evaluate the accuracy of the system we also chose to move with constant velocity along a straight line.The error in distance was measured to the line of the predefined route that is shown in the Figure 21 inthe result Section 6.4. The system error is investigated without dead reckoning in Figure 19, however deadreckoning is investigated separately in Figure 20.

Density of beaconsThe accuracy can be improved if additional beacons are integrated to the system. To analyze the affect ofthe density of beacons more beacons were added to the system, and the results were compared, se 6.4.

Lifetime of ZBeaconThe lifetime of the system is evaluated by measurements of the voltage used by the beacons. Because thereceiver is driven by an external source (a computer) the lifetime of the receiver is neglected. Ohms Lawin equation 7 is used to calculate the current consumption of the device. The voltage U is measured by anoscilloscope over a given resistance R, and thus the current is derived. The capacity of a battery is usually

26

given in Ah (Ampere-hours), and by dividing with the current consumption, the life time remains. This isillustrated in equation 8.

I = U/R (7)

t =battery capacity

current consumption(8)

27

6.4 Results

This section have a similar structure as that of System Verification: tests of individual devices and tests ofparts of the ZBeacon system are presented in subsections.

6.4.1 Device tests

This subsection cover results from tests about the different devices and units that are later to be integratedin the ZBeacon system. Each device is studied to investigate the capability of future designing of an IPS.

Distance tests outdoors at a field

The most important component in an IPS is the accuracy of the measurements. Therefore measurementtests were performed early to investigate possible accuracy of a future system, but also to validate the ideathat an IPS can be based on RSSI measurements and simple algorithms. This validation is also claimedpossible by [32]. Firstly, measurements for the ideal case were performed, or as close as there could be to theideal case. The placed picked for the measurements was on a field far from any disturbances or interferences.

Figure 13 illustrates RSSI measurements for 1, 2, 5 and 10 meter distances. Different output powers wereused and a mean of every individual power was calculated. The result clearly shows that the RSSI decreaseswith increasing distances.

The result in figure 14 indicates that packages from lower output power did not reach the receiver. At adistance of 10 meter, all the different output power received to the receiver. At a distance of 30 meter, theminimum output power that reached the receiver was the TxPower register setting 0x25, which correspondsto -18dBm according to the CC2530 Datasheet, see [31]. The minimum output power reached at 60 respec-tively 100 meter distances was 0x55, which corresponds to -12dBm.

When a constant power of 0x35 was used, the data presented in Table 5 was given. The mean RSSI wascalculated, and so was the path component, n. The used value for the path component when calculating thedistance was decided to 2, because that is a proposed value for calculations with measurements outdoors.The mean value of the path component was calculated to 2.0156 for distances every meter from 2 to 10.Out of the measurements, it is clear that without interference the devices seems promising to use in an IPStogether with a good propagation model for the signal, at least for smaller distances.

Figure 13: Result from distance tests outdoors, 1, 2, 5 and 10 meters

28

Figure 14: Result from distance tests outdoors, 10, 30, 60, 100 meters

Rotating receiverWhen the receiver from Wiotech was rotated around its own axis, result in Figure 15 was obtained. Theresult indicates that the radiation of the antenna is not evenly distributed.

Figure 15: Result from Rotating receiver, Wiotech device

The receiver at SmartRF05 was rotated with the same conditions as the device from Wiotech, and theresults in Figure 16 is more promising.

29

Table 5: Result from Distance tests outdoors, power = 35

Metersbetweendevices

Mean RSSI Path loss (n) Calculated distance Error

1 -98.01 - - -

2 -104.03 1.9998 1.9999 0.0002

3 -109.33 2.3726 3.6813 0.6813

4 -109.17 1.8528 3.6141 0.3859

5 -110.63 1.8048 4.2756 0.7244

6 -112.01 1.7991 5.0119 0.9881

7 -116.62 2.2015 8.5212 1.5212

8 -118.01 2.2141 10.000 2.0000

9 -118.01 2.0959 10.000 1.0000

10 -116.01 1.8000 7.9433 2.0567

15 -122.65 2.0951 17.0608 2.0608

20 -125.16 2.0868 22.7772 2.7772

25 -123.52 1.8248 18.8582 6.1418

30 -124.03 1.7615 19.9986 10.001

Figure 16: Result from Rotating receiver, SmartRF05

Comparison of Figure 15 and Figure 16 shows the difference in directivity of the different antennas. TheRSSI from the device from Wiotech differ with 25dBm, when the antenna at the evaluation board differwith 15dBm when rotating the antenna.

30

Test for antenna at transmitterWhen the radiation of the transmitter was investigated, the result in Figure 17 was given. The result indicatethat a lying position of the transmitter is slightly better. The result from Figure 17a also indicates that thetop of the device should be rotated 90 degrees counterclockwise, to avoid the poor coverage in RSSI.

(a) Transmitter standing (b) Transmitter lying

Figure 17: Radiation for transmitter

Accelerometer testThe acceleration of the movement in the x-axis is monitored and shown in Figure 18a. This is then

integrated and the result is shown in Figure 18b. The movement itself is shown in Figure 18c. Note that theacceleration below is only considered in one axis.

(a) Acceleration output (b) Calculated velocity (c) Calculated distance

Figure 18: Result from accelerometer and gyro data

6.4.2 System tests

Result from tests when all units are integrated to the ZBeacon system are presented in this section.

Move along a predefined routeThe result of the test when the receiver was moved along a specific route is illustrated in Figure 19 and Figure20. The blue line along the corridor represent the actual route and the blue stars represent the estimatedpositions, and the error in distance for every estimated coordinate is calculated as the closest distance to theroute (the blue line). The mean error in distance is calculated to 1.80 m when only ZigBee was used, and4.01 m using only dead reckoning.

31

The accuracy of the system is calculated as the largest error in distance, which resulted in an accuracyof 9.51 m for the system using only dead reckoning, and 3.23 m for the ZigBee system. Thus one can withhigh probability say that the estimated position is within the accuracy.

Figure 19: Estimated position using ZigBee system only

32

Figure 20: Estimated position using dead reconing only

The final results, see Figure 21, is achieved when both ZigBee and dead reckoning are integrated to createthe ZBeacon system. The mean error in distance was calculated to 1.01 m, and the accuracy 3.33 m. Theresults of the different tests are summarized in table 6.

33

Figure 21: Estimated position of ZBeacon system

Table 6: Summarized results

System Mean error [m] Accuracy [m]

ZigBee 1.08 3.23

Dead reconing 4.01 9.51

ZBeacon 1.01 3.33

Density of beaconsFigure 22a illustrates the result when a number of 6 beacons were used. The result is an mean error of 0.87

34

m. When the density of beacons was doubled (see Figure 22b), the mean error decreased to 0.42 m. Theresult is shown in Figure 22, and the result is summarized in table 7.

(a) Result from Density of beacons, normal (b) Result from Density of beacons, doubled

Figure 22: Density of beacons

Table 7: Summarized results from tests of density of beacons

Number fo nodes Mean error [m] Accuracy [m]

Normal 0.87 2.16

Doubled 0.42 3.60

Lifetime of ZBeaconFigure 23 illustrates the power consumption of a beacon when a message is sent. The current consumptionwas calculated from the data given in Table 8 with equation 7, given the resistance 10.05 Ω. The time ofeach event was multiplied with the current consumption during that event, and the sum of those productsis the total power consumption for sending a message. The power consumption when the beacon is in sleepmode is assumed to be zero, since it is just a few µA. A messages is sent every 100 ms, and the mean current

35

of the beacons was calculated to 1.53 mA. With a battery capacity assumed to be 1200 mAh, the life timecalculed with equation 8 result in approximately 782 hours, which is equal to 32.6 days.

Table 8: Result from oscilloscope

Event Time [ms] Voltage [mV] Current [mA]

Wake up 4 80 7.96

Prepare for sending message 0.75 300 29.85

Send message 1.3 650 64.68

Prepare for sleep 1.9 80 7.96

Figure 23: Power consumption of beacon. Data from oscilloscope.

36

7 Discussion

The devices used to setup the IPS are not designed for the purpose they are used for in this thesis. Thedevices were constructed as simple nodes in a WSN and therefor the components are chosen after the originalapplication, which does not suit an IPS completely. The most crucial component is the antenna, which inthe mobile device is important to get proper RSSI measurements. The antenna of the devices is not a goodchoice for an IPS since the angle of the RF-signal affects the signal strength greatly at the receiver. This isstrengthen by the result in Figure 15 and 16. For an IPS it is more important with an good omnidirectionalantenna than good signal strength.

Since the devices only have one antenna the choice to use AoA were not possible. Therefor RSSI wasthe only option of gathering data, which is well known to be inaccurate. A parameter that affects the RSSImeasurements is the temperature. Favorably the devices are meant to be placed indoors where the temper-ature are most often constant, but if the units should somehow be placed close to a window or in a draftthe measurements could vary depending on season. This is confirmed by [31] where the temperature hasbeen well investigated. However the most important thing to consider is the placement of the devices, withreference to the surrounding objects. It is known that metallic objects is reflecting RF signals greatly, andlarge metallic objects placed in the near field of the transmitter greatly affects the radiation pattern of thetransmitted signal.

One early idea in the designing of the ZBeacon was to utilize the capability of different output power.By transmitting the same package but with different powers the receiver would receive all packages that itis in range of receiving. The receiver can then get an approximate range to the transmitter. This is notpossible because there are only 16 different power levels available in the ZigBee devices, which would meanthat the accuracy would not be good enough. The capability of adaptive output power is useful only inenergy aspects for this purpose. In an adaptive system the beacons could adapt their power depending onthe distance to the mobile device, and thus minimize the power consumption. The sleep function of theZigBee device can be used in advantage when there are no mobile devices in the proximity.

An improvement of the system could be other type of devices, to be able to take advantage of and imple-ment more measuring techniques. A device with dual antennas could use the RSSI and AoA measurementssimultaneously, which implies that in some ideal cases only one transmitter is necessary for determine theposition. Such a device could know both direction and distance to each beacon in a 2D plane. An evenbetter device could use four antennas divided in pairs, where the pairs are cross polarized. As proven inearlier sections the measurements are inaccurate and full of errors. Therefor an antenna array could improvea system significantly.

As seen in Figure 18 the accelerometer is not useless for measurement of distances. The total distancemoved was 3 dm and with integration of the acceleration approximation 2.9 dm was measured, which makesit suitable for dead reckoning. With such good precision one could wonder why not use only dead reckoning.The answer is that an accelerometer can not be completely trusted. Drifting errors in the accelerometer willwith time give huge errors, which is proved in Figure 20. Dead reckoning is supposed to give a better accuracyof the system, which is contradicting the results in Figure 19 and 21 when introducing the accelerometer.

The method used for determining the error and accuracy is not the most accurate, and not even correctin some sense. If the estimated error is large, but still close to the route, the error is still seen as the distanceto the route and therefor small. Figure 22b clearly illustrates this, especially close to the beacon pairs. Thedensity of the estimated points gathers around the beacon pairs even when the route is followed in a constantvelocity. The reason this method is used is solely because its simplicity.

37

8 Conclusion

An IPS is not as trivial to construct as one can think. There is a reason why indoor positioning is still anarea of research, it is currently impossible to satisfy the requirements for all different applications. RSSIbased trilateration, which this project have focused on, is fairly satisfying in wide open undisturbed areas,and even in perfect environment hardware limits can cause inaccuracies in meters. It is impossible to answerthe question which system used for indoor positioning is the best, since it depends on initial conditions andrequirements on the final system. In some cases it is necessary to run multiple systems simultaneously toreach the requirements.

The system designed, constructed and evaluated in this thesis is not the most accurate nor the cheapest,but it works and it is relatively simple. The integration of the accelerometer could have been improvedif we possessed enough knowledge about sensorfusion. Currently when introducing the accelerometer theestimated positions along the path gets an lower mean error but worse accuracy, and Figure 21 shows asmoother following of the route.

38

9 Future work

The ZBeacon system can be improved in many ways. There would be interresting to se how different al-gorithm affect the performance of the ZBeacon system, and to find a better solution for integration of theaccelerometer. Another interresting thing to investigate is how much the output power affect lifetime andcoverage of the beacons.

The largest improvement would probably be to develop new devices, that are more suitable for an IPS.The antenna integrated in Wiotech’s devices are not even close to be suitable for positioning, even thoughthey have advantages suited for other applications. One possible development is to construct an antennaarray, from which there can be added further measuring methods to be integrated in the system. Therewould also be of interrest to customize the code used for the application in Z-stack, to make it more efficient.

39

References

[1] Gough Lui, Thomas Gallagher, Binghao Li, Andrew G. Dempster, and Chris Rizos Differences in RSSIReadings Made by Different Wi-Fi Chipsets: A Limitation of WLAN Localization, Finland, 2011

[2] Gao Li-peng, and Jiang Han-wen, A Strong Anti-interference Capability Location Algorithm Based onRSSI, China, 2012

[3] Hsieh-Chung Chen, Tsung-Han Lin, H. T. Kung, Chit-Kwan Lin, and Youngjune Gwon, DeterminingRF Angle of Arrival Using COTS Antenna Arrays: A Field Evaluation, Florida, 2012

[4] Nardi S., Pachter M., GPS estimation algorithm using stochastic modeling, Florida, 1998

[5] Antti Kotanen, Marko Hannikainen, Helena Leppakoski, Timo D. Hamalainen, Experiments on LocalPositioning with Bluetooth, Finland, 2003

[6] Erin-Ee-Lin Lau, Wan-Young Chung, Enhanced RSSI-based Real-time User Location Tracking Systemfor Indoor and Outdoor Environments, South Korea, 2007

[7] Andreas Schmidt-Dannert, Positioning Technologies and Mechanisms formobile Devices, Berlin, 2010

[8] Artur Baniukevic, Christian S. Jensen, and Hua Lu, Hybrid Indoor Positioning With Wi-Fi and Bluetooth:Architecture and Performance, Denmark, 2013

[9] Hui Liu, Houshang Darabi, Pat Banerjee, and Jing Liu, Survey of Wireless Indoor Positioning Techniquesand Systems, 2007

[10] Carlos Medina, Jose’ Carlos Segura, A’ ngel De la Torre, Ultrasound Indoor Positioning System Basedon a Low-Power Wireless Sensor Network Providing Sub-Centimeter Accuracy, Spain, 2013

[11] Ruey-Hsuan Lee, Jen-Chieh Wu, Shao-Hsuan Chang, Sheng-Fuh Chang, Chia-Chan Chang, Yi-MingChen, Radar Design for Wireless Indoor Positioning Applications, Germany, 2013

[12] Simon Haykin, Cognitive radar: a way of the future, 2006

[13] https://www.zigbee.org/, Acc. 2014-04-07

[14] http://www.ieee.org/index.html, Acc. 2014-04-07

[15] Kartik Rathod, Nilay Parikh, Aesha Parikh, and Prof. Vrushank Shah, ”Wireless Automation usingZigBee protocols”, India, 2012

[16] Yoshihiro Sakamoto, Yui Totoki, Takuji Ebinuma, Kenjiro Fujii, and Shigeki Sugano, Indoor Positioningbased on Difference between Carrier-phases Transmitted from Proximately-located Antennas of a Multi-channel Pseudolite, Japan, 2012

[17] Md. Shariful Islam, Richard Klukas, Indoor positioning through integration of optical angles of arrivalwith an inertial measurement unit, South Carolina, 2012

[18] http://www.4gamericas.org/index.cfm?fuseaction=page&sectionid=2420, 2014-04-10

[19] Veljo Otsason, Alex Varshavsky, Anthony LaMarca, and Eyal de Lara, Accurate GSM Indoor Localiza-tion, 2005

[20] Christian Gentner, Estefanfa Munoz, Mohammed Khider, Emanuel Staudinger, Stephan Sand, andArmin Dammann, Particle Filter Based Positioning with 3GPP-LTE in Indoor Environments, SouthCarolina, 2012

[21] Chris Rizos, Gethin Roberts, Joel Barnes, and Nunzio Gambale, Experimental results of Locata: A highaccuracy indoor positioning system, Swizerland, 2010

40

[22] Jeffrey Hightower, Gaetano Borriello, and Roy Want, SpotON: An Indoor 3D Location Sensing Tech-nology Based on RF Signal Strength, 2000

[23] Lionel M. Ni, Yunhao Liu, Yiu Cho Lau, and Abhishek P. Patil, LANDMARC: Indoor Location SensingUsing Active RFID, Texas, 2003

[24] http://quuppa.com/, Acc. 2014-08-11

[25] http://www.senionlab.com/, Acc. 2014-08-11

[26] http://www.teletracking.com/, Acc. 2014-08-11

[27] http://www.wiotech.se/, Acc. 2014-08-11

[28] http://www.ti.com/, Acc. 2014-08-11

[29] http://www.iar.com/, Acc. 2014-08-11

[30] Bicsi, B., Network Design Basics for Cabling Professionals. City: McGraw-Hill Professional, 2002

[31] Texas Instruments, ”A True System-on-Chip Solution for 2.4-GHz IEEE 802.15.4 and ZigBee Applica-tions”, CC2530 datasheet, Apr. 2009 [Revised Feb. 2011]

[32] Shi Shuo, Sun Hao and Song Yang, Design of an experimental indoor position system based on RSSI,China, 2010

41