Design and implementation of a localization system based on a RF multipurpose platform

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Design and Implementation

of a Localization System

Based on a RF

Multipurpose Platform

by

Luz Karine Sandoval Granados

Thesis submitted as partial requirement for the degree

of

MASTER OF SCIENCE IN ELECTRONIC

ENGINEERING

from

Instituto Nacional de Astrof´ısica, ´

Optica y

Electr´

onica

October 2011

Tonantzintla, Puebla

Supervised by:

Ph.D P. Jorge Escamilla Ambrosio, Ms.c Jorge

Pedraza Chavez, INAOE

c

INAOE 2011

The author gives permission to the INAOE to

reproduce and distribute copies in whole or in parts of

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.

“ To my beloved parents

To my dear sister Laura ”

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Acknowledgment

I would like to express my gratitude to people who had helped and inspired me during my master study.

To my Teachers, my advisor Dr. Jorge Escamilla and also the members of instrumentation

de-partment, they instruct me and advice me during this two years, I am sure that their knowledge and comments influence this work in a positive way.

To my friends and colleges on Electronic’s Department at INAOE, special thanks to Hector,

Jhoan, Fabian and Jaqueline who have been a real support during my stay in this country. Also I am grateful to Erika, Moises, Abel, Jesus, Dulce, they thought me a quite part of the Mexican culture and also made of those two years a joyful and enrichment experience.

To my family, for their support and encoragement throught my entire life and in particular, I am

grateful to my syster Laura, whose assistance was an important asset to this thesis.

To the Consejo Nacional de Ciencia y Tecnologia (CONACYT-Mexico) for providing me with

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ABSTRACT

TITLE:Design and Implementation of a Localization System Based on a RF Multipurpose Platform

AUTHORS: LUZ KARINE SANDOVAL

KEY WORDS:RSSI, Wireless location system, Location awareness, Neural Networks, Multilayer

Perceptron.

DESCRIPTION:In this work the development of a radio frequency (RF) indoor location systems

using Texas Instruments device ez430-RF2500 is proposed, this kind of systems are commonly used to perform many monitoring and tracking tasks. They pose a real challenge because for indoor en-vironments the RF model of propagation is much more variable than that for outdoors environment: signal levels vary greatly depending on specific features such as the layout of the building, the con-struction materials and the positions of the sensors.

The development proposed in the paper was designed to work with basic tools, practical consi-derations such as the small size, cost and power constrains were taken into account. A fixed set of low-cost, low-power transceivers together with information commonly available as Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) were used to convey a proper response.

The algorithm proposes is based on a neural network approach. A Multilayer Perceptron is trained off-line to learn the relationship between the local position of a mobile node and the common features of a packet received (RSSI and LQI) from four base stations (anchors).

The tests showed promising results, twenty one fixed points were evaluated in a closed room (3.9m x 7m), four base stations were transmitting continuously in different channels and a mobile node took in time intervals the RSSI and LQI from packets received from each anchors.

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List of Figures

1.1 Example of a Location Awareness System . . . 3

1.2 Relationship between distance T-R and coverage area [13] . . . 4

1.3 Field Regions for transmissions using a typical antennas . . . 5

1.4 Mechanisms of propagation waves . . . 6

1.5 Synoptic Diagram Section 1.1 . . . 9

1.6 Synoptic Diagram Section 1.2 . . . 9

2.1 Development Kit Texas Instrument ez430-RF2500 . . . 14

2.2 Simple MSP430-CC2500 interconnection diagram [22] . . . 15

2.3 Packet Structure . . . 16

2.4 Communications Protocol [24] . . . 17

2.5 Waspmote Development Tool . . . 18

2.6 Waspmote API header . . . 19

2.7 Frontal-face of a location system, Angle of Arrival Technique . . . 20

2.8 PinPoint Calibration Phase . . . 22

2.9 Interferometry Technique . . . 23

2.10 AOA Interferometer . . . 24

2.11 Trilateration . . . 24

3.1 Measuring Transmission Time on Waspmote Devices . . . 28

3.2 Connection Diagram . . . 29

3.3 Details of Current Consumption on ez430-RF2500 . . . 30

3.4 Antenna’s Radiation Pattern of TI ez430-RF2500 [41] . . . 34

3.5 Rutine for each Base Station . . . 36

3.6 Algorithm used in the mobile device . . . 37

3.7 State Machine of Mobile Unit . . . 38

3.8 Identifier of a new point . . . 39

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viii LIST OF FIGURES

3.10 Presentation of printed data . . . 40

3.11 Algorithm used in the gateway . . . 41

4.1 Experimental SetUp . . . 46

4.2 RSSI as a function of distance. . . 47

4.3 RSSI as function of distance . . . 48

4.4 Measuring the RSSI at fixed point . . . 49

4.5 Filtering Process: (a) Signal in time domain; (b) Effect of impulse train; (c) Frequency Response . . . 49

4.6 Experimental Testbed . . . 50

4.7 Effect of antenna’s anisotropy on RSSI measures - Test 1 . . . 52

4.11 Attenuation Pattern in a Crowded Place . . . 56

4.12 Neural Network Estimations on Different Points . . . 60

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List of Tables

1.1 Relevant RF Positioning System . . . 12

3.1 Test results . . . 29

4.1 Results of The Neural Network Training . . . 58

4.2 Results of Neural Network Validation . . . 59

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Chapter 1 Introduction

Wireless communications as a foundation of a localization system, has been a widely researched technology that offers a reliable and low cost system. Its popularization began with the invention of mobile phones, devices that in few years have gotten to root in people, being today an indispensable item for most of the population [1], it is in continuous improvement at an extent that new features and technologies are constantly added.

The widespread success of wireless communication has led to the development of a quite signif-icant number of systems and standards that enable transmissions between different kind of data and devices. Today it is possible to transmit audio, text and video at high rates and at reasonable levels of security and reliability, popular systems like Bluetooth and Wireless Local Area Networks (WLAN) are the result of this intense research, they made easier the communication between devices in such way that there are an explosive growth of wireless devices like printers, headphones, microphones, speakers, keyboards, which all have now their wireless version [2].

Because of these new devices have become simultaneously less expensive and more powerful, many paradigm shifts have taken place, wide variety of sensors allow the measurement of different conditions including: temperature, pressure, humidity, speed, motion, distance, light and proximity. Therefore, the development of more practical and dynamic systems is now possible and then the research has been orientated to personalized environments.

Personalized environments require devices that can passively or actively determine their location, the location awareness (term used to refer to this kind of devices) is a highly targeted market opportu-nity. This is because the location awareness gives meaning and context to measures taken, it introduces a new field of application in many areas: wireless security, monitoring and tracking systems are the most popular. This technology is needed in any system that delivers information to users based on their physical location.

Nowadays, there are multiples ways to identify where is a mobile target. Basically, these systems use some type of wave (infrared, radio frequency, ultrasonic, etc.) and relate its features (amplitude,

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2 Introduction

frequency or phase) to distance. Various technologies are available: GPS (Global Positioning System), cellphone infrastructure and wireless access points, but neither of them have been labeled as ”the best”. There are many constrains and restrictions in this problem: power consumption; range and accuracy of sensors devices; protocols and methodologies needed to support the distributed signal processing and information storage [3,4], are some examples. Most of all these systems have been designed without taking into account the environment, which represents the biggest one restriction, wave’s diffraction, reflection and scattering is highly affected by it.

The favorable features described in the last paragraphs, motivated the research work presented in this thesis, which addresses the development of a location system that, considering different con-strains, make it feasible for many applications. This development was designed to work in indoor environments with basic tools, practical considerations such as small size and low cost were taken into account. A methodology based on hardware constrains and the different approaches proposed in literature were used to define each element of this system. A review of the features of this system are presented in the following paragraphs.

A fixed set of low-cost, low-power transceivers as the Texas instruments ez430-RF2500 and also information commonly available as Received Signal Strength Indicator (RSSI) and Link Quality In-dicator (LQI) were used to convey a proper response. The algorithm proposed is based on an off-line training technique as the neural network approach, the Multilayer Perceptron approach is employed to establish the relationship between the local position of the mobile node and common features of a packet received (RSSI and LQI). Once the system is trained, on-line location can be performed.

1.1 Basic Concepts

1.1.1 Definition

A location awareness system (figure 1.1) is a wireless sensor network that uses a number of observable parameters (angle, velocity, signal strength) to determine the position of a target. This collaborative process has three basic components:

Base Stations: These elements are generally transmitters of radio, infrared or ultrasound signals,

they act as passive components emitting continuously this type of wave. Satellites, GSM towers or Wi-Fi access points are some examples of them.

Terminal devices: They play a crucial role in positioning systems, as the system’s target, they

act sometimes as transmitters and receivers depending on infrastructure and protocols. These devices usually have a small size, mobility and low power consumption; mobile phones, Wi-Fi enabled tags, laptops, PDAs and hand-held GPS receivers are the most popular.

Control Unit: It manages the information and carries out the signal processing, depending on

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1.1 Basic Concepts 3

Base Station

Data Transmittions

Bidirectional Communications

Base Station Terminal

Device

Control Unit Base Station

Base Station

Figure 1.1: Example of a Location Awareness System

independent device, which performs the processing of all the information (centralized system).

1.1.2 Drawbacks of Electromagnetic Wave Propagation

Most positioning systems make use of wave propagation theory to determine the target position, some of them use time difference of arrival to do this approximation [5,6], others use the signal strength [7–9] or a combination of them [10,11], however, the propagation itself have many drawbacks, as is explained in the following sections:

Free Space Path Loss

When receivers and transmitters have a clear, unobstructed line-of-sight (free space propagation) the power of wireless transmission decrease with the square of the distance [2,12], this statement is based on the fact that electromagnetic waves propagates in all directions covering the surface area of a sphere (Fig 1.2), then as a wave propagate out from the source its radiant energy remains the same, but the energy per unit area (energy density) decreases.

In communication systems, the free space propagation model takes into account others parameters like antenna’s features and intrinsic system losses. This relationship is described by the Friis free space equation,

Pr(d) = PtGtGrλ 2

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4 Introduction

Receiver

S1

S2

S3

Transmitter

Figure 1.2: Relationship between distance T-R and coverage area [13]

wherePr(d)andPtdenote the received and transmitted power,GtandGrare the antenna gain in transmitters and receivers,λis the wavelength,dis the transmitter-receiver separation distance andL

is the system loss due to transmission line attenuation, filter losses in the communication system. Equation 1.1 shows how sensitive is a communication system. The signal attenuation (path loss) is an important parameter in a proper design, it is defined as the difference between the effective transmitted power and the received power [2] and is measured in dB. The intrinsic path loss is given by:

P L(dB) = 10logPt

Pr

=₋10log[GtGrλ 2

(4π)2_d2] (1.2)

Free Space Model Constrains

Propagation of electromagnetic (EM) waves imply the interaction of electric and magnetic fields through a medium (metals, water, air, etc.). If EM waves change its propagation medium (for ex-ample when these waves leave the guiding influence of wires and move to space), then this cause disturbances in the EM fields. This behavior can be categorized as a function of distance, where three boundary regions are defined (Fig 1.3), these regions are: the ”Near-Field”, ”Transition Zone”, and ”Far-Field” [12].

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1.1 Basic Concepts 5

Transition Far Field Near Field

Zone

Figure 1.3: Field Regions for transmissions using a typical antennas

When the distance between source and receiver is too small (less than 2λ approximately), the

energy from the source is not radiated in a radial direction, then other effects have to be taken into account in order to do a proper model [12]. This is because the relationship between the electric field

(E) and the magnetic field (H) becomes very complex; this regions are known asNear-Field when

distance is less thanλandTransition Zonewhen the distance is betweenλand2λ[12,13]. The Far-Fieldor Fraunhofer region is the operation region where most propagation models are proposed (the Friis free space model only makes a proper prediction in this region [2]). The distance traveled by EM waves in this region is enough (farther than two wavelengths) to guaranty stable electric and magnetic fields (The E and H fields are mutually perpendicular to that direction and to each other) and, because of the linear relationship between its fields, many approximations can be done [2,12].

Multi-propagation Signal Effect

Wireless communication systems have one fundamental limitation, their transmission path has many uncertainties; it can vary from simple line-of-sigh to one that is severely obstructed by different objects (buildings, foliage or people). The transmission is affected by three basic propagation mechanisms (Fig 1.4):

* Reflection: Occurs when a wave changes the transmission medium, in this case the reflection

takes place when the wave impinges an object big enough that its dimensions overcome the

wavelength of the propagating wave [2]. As a consequence, part of the wave bounces off and

changes its current direction.

In electromagnetic waves, the reflection coefficient is highly influenced by the obstacle’s con-ductivity; when the plane wave imping a perfect dielectric, part of its energy is reflected and the remainder is transmitted, but when the obstacle is a perfect conductor, all the incident energy

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6 Introduction

Reflection

source

(a) Reflection [14]

Scattering

source

(b) Scattering [14]

Diffraction Aperture through

source

Shadow

Zone _around

Obstacle Diffraction

(c) Diffraction

Figure 1.4: Mechanisms of propagation waves

is reflected back into the original medium [2]. It makes the estimation of this phenomena a

hard issue, daily objects are made of more sophisticate materials, and the reflection coefficient (Fresnel reflection coefficient) also is function of the angle of incidence and the frequency of the propagation wave.

The wave reflection phenomenon is one of the biggest problems in wireless communications systems, it causes a phase reversal, so when a message is transmitted, the receiver will see a combined signal (one component is the line-of-sight signal and the others are produced by re-flections). This effect could be very harmful for the system, with proper conditions ( path length of the reflected signal and wavelength) a interference constructive or destructive is possible [12].

* Diffraction: It is a phenomenon present when waves pass through an opening or around sharp

irregularities, it produces secondary waves that allow to surround obstacles or pass through openings. The amount of diffraction depends on the wavelength and the sharpness of edges, if the wavelength is smaller than the obstacles there isn’t any effect [2].

Huygen’s principle can explain why diffraction is produced, it states that any point of the wave-front is a source of a secondary wave. Thus, diffraction is useful because permits wireless communications between points where the transmission path is obstructed by objects opaque to radio waves (mountains, buildings, etc.) [2,12].

* Scattering: It is a mechanism of propagation induced by the roughness in different obstacles, when a wave imping this kind of surface the signal diffuse in all directions adding more spurious

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1.2 State of the Art 7

signals to the spectrum [2,12].

The amount of scattering is influenced by the degree of roughness, wavelength (λ) and the angle of incidence (θi). The maximum height (hc) of this protuberances is given by the Rayleigh criterion 1.3. Many common objects such as lamp posts and trees tend to scatter energy so, this phenomenon is present in all wireless communications [2].

hc=

λ

8sinθi

(1.3)

As it has been seen, the environment in a wireless communication system has many signals trav-eling over multiple paths; reflection, diffraction and scattering are unavoidable. Thus, the receivers have to be designed to resolve variations of signal strength, frequency distortion, time delay spread and fading [12].

1.2 State of the Art

1.2.1 Indoor and Outdoor Environments

Real time localization systems can be classified depending on the environment where they are used, in-door and outin-door applications are very popular, however, they suppose different challenges. Outin-doors systems require an expensive infrastructure, their mobile devices need an excellent power management and a wide coverage area. Besides, their base stations have to be designed to endure different envi-ronmental conditions (humidity, strong winds, rain, etc). On the other hand, indoor systems require more signal processing, their model of propagation is much more variable than outdoor environments, specific features such as the layout of the building, the construction materials and the positions of the sensors produce multiple signal propagation [2].

Wide coverage areas have already an almost reliable system, the GPS has been integrated to many devices such as smartphones, automobiles, personal computers, airplanes, to name a few. GPS is a worldwide system based on 24 satellites, located around 30000 km above the Earth’s surface, they orbit at 11000 nautical miles and send their current coordinates at GPS receivers, which use this information to estimate their position by trilateration. This technique needs at least three satellites with line of sigh to get a reasonable accuracy response (less than 10m) [15].

In closed areas, many systems have been proposed, which vary in different aspects like the infras-tructure, protocols and technology used (it can be Infra-Red (IR), ultrasonic, bluetooth, ultrawide-band or Radio Frequency (RF) [1-4]). Analyzing the wide range of possibilities it is found that IR based systems have an accuracy of 0.07 meters at the expense of cost in terms of hardware, power consump-tion and coverage area. In the same way, ultra-wideband systems have also an small estimaconsump-tion error (around 0.1 meters) but its performance is restricted by the Federal Communication Commission due

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8 Introduction

to the hight power transmissions [15]. Moreover, many others systems have been proposed which

illustrate the fact that accomplishment of an excellent performance is not a warranty of a successful solution.

1.2.2 Radio Frequency Approach

In real applications different conditions have to be taken into account in order to stablish the real feasibility of the system, this conditions are not only limited by the environment, the infrastructure itself could compromise the performance, therefore, an adequate integration of hardware and software in addition to robust communication protocols are needed; one possible short cut to this problem is the use of a mature technology, like the use of radio frequency devices.

The RF transceivers have all kind of support due to its continuous research, and more important, its successful implementation on printed boards, which offers many advantages like portability, low costs and low power consumption in addition to the inherent benefits of using RF waves [7]. In table 1.1 the different implemented proposals illustrating the adaptation of this technology are presented.

1.2.3 Overview of the Different Approaches

Table 1.1 is a summary of the most relevant RF positioning systems proposed up to date, as it is seen, the development started in 2000 with RADAR, a location technology that get the estimations using a two fold approach; one of them is based on a propagation model enhanced with some empirical variables and the other one uses a fingerprinting of the environment. The maximum error obtained in RADAR is about 4.3 meters. Nevertheless, this error could be considered as acceptable if the coverage range is taken into account. In this particular system, the error change at 200 meters with line of sight, at 50 meters in a semi-open place and at 25 meters in a crowed place. Despite the quite big error obtained, this was a promising result because few constrains were taken into account.

The analysis of different sources of noise and distortion were not included in RADAR, but this is a real challenge in current systems. Subsequents technologies considered different kinds of inter-ferences, for example, COMPASS and EKAHAU use probabilistic algorithms to deal with human obstructions and movements, the accuracy achieved is now around 1 to 3 meters, but still depends a lot on the environmental conditions. The next step was to incorporate prediction algorithms, it was done by HABITS which claims to be able to enhance any positioning system by incorporate the patron behavior of people. In the EKAHAU system, HABITS increases the precision of the system, allowing accuracy estimations in blind spots.

Other lines of investigation aimed to get good results by changing the infrastructure. Systems like SPOT-ON are autonomous devices that perform all the different tasks of a positioning system, however, the localization can be only obtained as a relative distance to other users, thus, the accuracy

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1.2 State of the Art 9

depends on the size on the group.

Appreciable differences (in hardware and software) on proposed systems can be observed when the measuring distance technique is changed. For example, the use of the time of arrival technique need in most RF based approaches the use of additional hardware. The interferometric approach also needs another changes but this time at a software level (special protocols and settings have to be set) in order to stablish the proper conditions to produce the desired signal, however, the accuracy is better (around 0.12 meters) but the requirements are high. As a consequence, before choosing the general features of this work, it is imperative to understand each one of the different approaches.

On figures 1.6 and 1.5 a summarize with the main find outs discussed in this chapter are presented.

{

* Diffraction * Reflection

* Scattering

{

parameters like signal strength, time of flight or phases differences.

{

Physical Phenomena Involved:

Environment:

* Outdoors

* Indoors Still open research problem GPS become the standard

Technology Employed: Wireless RF devices

Objetive: Determine the local position of a transceiver by the use of signals observable

* Mechanism of waves propagation

* Attenuation _{* Friis Equation}

Wireless Location System

Figure 1.5: Synoptic Diagram Section 1.1

{

_{

{

Wireless RF Indoor Location System

* 802.11 Infrastructure

{

* Own Infrastructure

Infrastructure:

{

Operational Mode:

* Estimation Phase

* RSS

* Propagation Model * TOA

* AOA

{

* Measure Phase

{

Statistical Methods.

* Fingerprinting Statistical Methods. + Lateration Neural Networks

Statistical Methods. Lateration * AOA or TDOA Algorithm

* Pinpoint * Lanzisera * Radio Interf AOA * Spot−ON * RFID * Telosb

* RADAR * Trapeze * COMPASS * In−building * EKAHAU * HABITS

Lateration

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10 Introduction

1.3 Research Objectives and Organization of this Document

1.3.1 Problem Definition

A positioning system for indoor environments is still an open research problem that requires the con-sideration of multiple factors, the main constrains is the environment where this system will be im-plemented, any object with sharp edges or rough protuberances could be a source of multipath or attenuation, inherent properties as the conductivity of the material where the wave impinges is also an important parameter that determine the percentage of the energy transmitted or reflected. Therefore, diffraction, reflexion and scattering are unavoidable effects on signal’s propagation when the condition of line of sight cannot be guaranty,

These undesired effects make the task of modeling the wave propagation a hard issue, where random variables have to be incorporated. To overcome this constrain, many proposals have been done, all kind of variables have been used like RF, IR, or acoustic signals but neither of them can guaranty a hight accuracy at reasonable costs.

The best results were obtained when additional hardware was incorporates, making indeed, a highly accurate system. But at extend that it cannot be considered a feasible option, its costs and fea-tures could restrict its massive implementation. Then, the objective of this work is design a positioning system employing a commercial off-the-shelf RF development tool as start point.

As can be seen from above discussion, the design of a positioning system implies a careful selec-tion of each one of the basic elements of this applicaselec-tion, that can be cope with the inherent uncertain-ness produced by the wave propagation in any wireless system.

1.3.2 Objectives

General Objective

The objective of this research is to design an indoor positioning system based on a commercial off-the-shelf multipurpose RF development tool that using only the information provided by the com-munication system of these devices will be able to determine the local position of a target in a real environments like an office or a closed room.

SSpecific Objectives

* Evaluate the performance of two multipurpose RF development tools as Libelium Waspmote and Texas Instrument ez430-RF2500 in order to determine the feasible use of them in a posi-tioning system.

* Analyze the different approaches proposes in the literature in order to determine which of these techniques are suitable for the hardware provided.

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1.3 Research Objectives and Organization of this Document 11

* Create the necessary protocols to ensure a proper operation of the positioning system.

* Make experimental tests in order to discard and select a suitable technique.

* Carry out experiments on controlled and crowded environments to test whether the different proposals can be used with the provided platform.

1.3.3 Organization of this Document

The remainder of this thesis is organized as follows, Chapter 2, presents a description of the different elements of a RF localization system, which will be useful to stablish the different techniques that can be implemented. In chapter 3 some tests and further analysis over the hardware allowed to define the features of this system. In chapter 4 some experiments are carried out in order to evaluate the performance of the proposed approach and finally the conclusions and future work are discussed in chapter 5.

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12 Introduction

Ref. Technology

Name Accuracy

Dist. Measuring Techniques

Loc. Estimation

Techniques Infrastructure Year

[7] RADAR 3 - 4.3m RSS & SNR -Database -Base stations (BS) 2000

-Prop. model -WLAN devices

[16] Spot-ON Depends on RSS -Empirical Model -Relative location 2000

cluster size -Triangulation to other devices

[15] Trapeze 10 - 25ma _RSSI _{-Fingerprinting} _{-Server on 802.11} ₂₀₀₀

LA-200 Network + Wifi tags

[15] RFID 0.25 - 4.19m AOA Range & Angle -Reader + Antennas 2005

Radar measurement -Passive Tags

[17] Lim, Kung 3m RSS Euclidean distance -802.11 Infrastruct 2005

Hou, Luo client - nodes - Wifi devices

[5] PinPoint 1.27 - 4.27m TOA RF Lateration -Base stations 2006

-Tag Hardware

[18] COMPASS 1.65m RSS -Fingerprinting -WLAN infrastruct. 2006

-Prob. Algorithmb _{-Digital compass}

[8] In-building 1.18 - 2.16m RSS Neural Networks - 3 Modems 3COM 2006

- 1 Laptop

[6] Lanzisera, 1 - 3m TOA Hardware App. - 2 Sensor Motes 2006

Lin, Pister

[9] Adaptive Dist. 0.5mc RSSI -Statistical methods - 7 Base Stations 2007

Estimation -Artificial Neural N. - 1 Mobile Device

[15] EKAHAU 1 - 3m RSSI -Fingerprinting -802.11 Network 2008

-Prob. Algorithmd _{-Tags + Wifi clients}

[19] Paschalidis, 2.26m RSSI Pdf Interpolation 30 Motes doinge ₂₀₀₉

Li, Guo Prob. Descriptors a dual function

[20] Telosb 2.23m RSSI Neural Network - 3 Active BS 2010

Neural App. LQI - 1 Mobile mote

[11] RF Received 0.05 - 0.12m Radio Inter- Phase differences -2 transmitter nodes 2010

Phase ferometricf _Algorithm _{- 1 Receiver}

[10] Radio Interf. 3 degrees AOA Radio Interf. - Array of 3 motes 2010

AOA measurement - 1 target

[21] HABITSg Predictability Software Bayesian Filter EKAHAU 2011

80% Tool System

Table 1.1: Relevant RF Positioning System a

This low accuracy is compensated by its wide coverage (around 4000 devices at once) b_{Reduce effect of human body}

c

Under specific conditions d

Reduce Error of human movements and wall effects e

Placed on differents landmarks to construct the pdf families f

Only works using Berkeley Mica2 Motes have been reported

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Chapter 2 Structure of a Positioning System

In the last chapter location awareness systems were presented, their features and constrains reveled that it is not possible to reach a general solution to this problem, it had to be delimited in order to attain reasonable results. In principle, a discussion about the work environment and technology used in different proposals were done. The indoors approach and RF technology was chosen considering that this kind of system aims to resolve an open research problem employing a well supported and low cost system as RF transceivers. Once the system was defined, a review of the different alternatives in this field was done, this study allowed to identify the different features of a Location Awareness System, which have to be taken into account in order to make a proper design.

In this chapter the basic structure of a positioning system is presented, as well as the different strategies employed on each of these elements, which will be the base for a proper system selection.

2.1 Infrastructure

This approach is intended to operate under a wireless development platform, this platform offers excellent resources, its design promotes the development of complete projects without many concerns about different protocols and subsystem interfaces. They got it, combining the performance of a micro-controller with other commonly available input/output systems, as is the case of ADCs, pushbuttons, RF transceivers, etc.

The system is basically composed by gateways and boards, a gateway constitutes a bridge be-tween incompatible hardware like laptops and transceivers, which otherwise could not be able to communicate. On the other hand, a wireless board has an autonomous system that allows monitoring tasks of almost any kind of variables, due to the different input/output ports and the multichannel RF transceiver integrated.

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14 Structure of a Positioning System

(a) Debugging Device and Target Board.

(b) Battery Case.

Figure 2.1: Development Kit Texas Instrument ez430-RF2500

2.1.1 Texas Instrument ez430-RF2500 development tool

The ez430-RF2500 development tool was specially designed for remote monitoring applications, it has an entire set of tools which enable the implementation of complete projects without much effort. Figure 2.1 shows the components of the basic kit:

* Battery Board: It is basically a case where two AAA batteries are connected in order to keep the necessary current powering the target board, enabling portability of this system.

* USB debugging device: It acts as the gateway of the system, it is responsible for communications between laptops and target boards. It has multiple functions in order to properly debug appli-cations using IAR Embedded Workbench Integrated Development Environment (IDE) or Code Composer Essentials (CCE).These tools allow also to analyze programs at low level (changes of different registers instructions by instructions), reaching more efficiency when program opti-mization is necessary.

* Target Board: The target board constitutes the heart of this device, it has the whole communi-cation system (RF transceiver, antenna, crystal, etc), the different input/output ports and also a microcontroller that manages and saves the instructions codified. The target board is removable

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2.1 Infrastructure 15

(see figure 2.5(a)) so once a reliable code is realized, the next step is to compile and debug it in order to save it on the target’s microcontroller, unfortunately it has a limited memory, thus the efficiency of programs is the main concern.

Programming and Compilation

Assembler or C++ can be employed as coding languages. For this reason, the communication between the MSP430 and other input/output systems like the CC2500 are done through registers, this level of instructions is too low so in order to facilitate the coding task, different libraries were created. Thanks to that, the port configurations (UART settings) were not necessary done by the final user, only basic settings have to be specified like the data rate of transmition to the USB port. Other useful libraries simplify the change of the different radio settings.

Communications with the RF Transceiver CC2500

Communications are enabled by the RF transceiver CC2500, which is a flexible system that allows different settings, for example, it is possible to change the bandwidth and frequency of the channels, the power of transmissions and the kind of modulation that will be used. All of this features can be configured depending on the MSP430 instructions. In figure 2.2 a diagram of the different intercon-nections between the MSP430 and the CC2500 are shown, four of this six wires form the serial link (SPI) responsible for enabling digital communication.

MSP430 _CC2500

Clock

SPI Serial Interface

4 wires Digital Communication System Interruption

User Interruption

Output Ports conected to interruptions F2274

Figure 2.2: Simple MSP430-CC2500 interconnection diagram [22]

As a consequence, the whole communication is enabled by a set of instructions that have to be defined each time a wireless application is carried out. However, a software tool was developed to make easy the task of changing the different settings that the communication system has. The SMART

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RF STUDIO has a wide variety of transceivers integrated to the Texas instrument development tools to choose, it allows the configuration in two modes, this tool allows to establish different RF parameters an also to set data rates of packets to be transmitted.

Transmissions and Reception

The transmissions and receptions are limited by the size of the packet (the maximum size is 64B), however, there are a wide variety of transmission modes supported, burst and continuous transmissions are available, but this only increases the number of packets to transmit [23]. The CC2500 provides an useful support for packet handling. In the figure 2.3 the diagram of the packet format is shown. In this architecture, additional information like sync word, preamble and length field must be included for the demodulation process, but it is possible to send additional information like Cyclic Redundancy Check (CRC) and the address byte.

Address Field

8xn bits

System Fields

packet.frame (User provided fields) Data Field

destination payload

8bits

Lenght _source 8xn bits 16bits

16/32bits CRC

Sync Word

PREAMBLE

Figure 2.3: Packet Structure

Communications Protocol

The target board is a very flexible hardware that can be manage by registers, this feature enables the development of partial or complete protocols depending on the specifications required. By default the SimpliciTI protocol is used, it is a low-power RF protocol elaborated by Texas Instruments that enables RF transmissions and receptions in a simple way. Its architecture is shown in figure 2.4, three basic layers can be identified:

* Application Layer: in this layer the specific protocols and methods to support peer to peer

communications are established, most of them are not intended to be part of the customer de-velopment environment, its functions are more related to security and reliability of wireless connections [24,25].

* Network Layer:The Network Layer has only management tasks, it is responsible for the routing of packets transmitted and received [24].

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DATA−LINK

* Ping: debugging purposes.

* Link: Support link management.

* Joint: Guard entry to network.

* Security: control encryptions keys.

* Mgmt: general management.

Management Layer NWK

DRIVERS: C Lybraries MRFI − BSP APLICATION

LAYER

NETWORK

PHY

Figure 2.4: Communications Protocol [24]

* Data Link/PHY:this layer is composed by two entities, the Board Support Package (BSP) and

the Minimal RF Interface (MRFI), both of them provide the necessary functions to allow the im-plementation of a common API for all supported RF and Board devices. Basically it constitutes a set of libraries that make easy the programing of target boards [24,25].

2.1.2 Libelium Waspmote Devices

The Libelium Waspmote hardware technology (figure 2.5) is a development tool designed and manu-factured to be used by a diverse audience (engineers, system integrators and also consultancy compa-nies are part of the end users), for this reason it offers a complete set of additional modules that can be easily integrate to the target, in order to expand the functions of this devices without many concerns about the interfaces needed to warranty a proper operation. In Figure 2.5(c), the available sockets are shown. It also offers different input/output options, like and UART connector, a USB port and also the traditional analog and digital ports.

Thinking on this project, the following tools are necessary:

* XBee 802.15 Module: this device allows wireless communications under the standard IEEE

802.15.4, which defines the physical level and the link level, operating at 2.4GHz in 16 channels with a bandwidth of 5 MHz. The power of transmissions is adjustable on five levels (-10 dBm to 0 dBm).

* Battery: Waspmote uses a rechargeable lithium-ion battery with 3.7V nominal voltage.

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(a) Waspmote Board (b) Waspmote Gateway

(c) Board Frontal Face (d) XBee Module

Figure 2.5: Waspmote Development Tool

receive data from remote motes as well as to modify or to consult the XBee’s configuration parameters.

* Waspmote Boards: This device is the main part of this kit, it is responsible for monitoring

tasks in remote places. It manages different elements as battery, Xbee modules and sensors board (accelerometers, temperature or presion sensor) using a microcontroller ATmega 1281 and expandable memory (SD card).

Programming and Compilation

In order to create and loads projects, Libelium developed a set of useful tools:

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Waspmote devices, such as interruptions or transmission channels, this API has been developed in C/C++ and it is divided in classes and data structures (a total description can be found as part of wasp-mote support [26]). This instructions facilitate the programming process because it includes of all modules integrated in Waspmote, as well as the automation of routine tasks.

Waspmote-IDE compiler: this software was developed by Libelium as part of the Waspmote sup-port, it is an useful tool designed to operate under Linux, Windows or Mac-OS, It makes possible create, compile projects and also allows to see the data present on the serial port.

Transmission and Reception

Transmission and reception functions are realized by an independent module integrated to the Wasp-mote Board. This element can be chosen by the user, depending on the project’s requirements, there are a wide variety of mudules, they differ in some aspects like technology, communication protocol or power transmission. However, this work was realized with the XBee 802.15.4 modules.

The whole management is done by Waspmote Libraries. In this case the Waspmote XBee files (WaspXBeeCore.h; WaspXbeeCore.cpp, WaspXBee802.h and WaspXBee802.cpp) are required. These libraries contain the necessary functions to set different features of the system like the protocol, model and frequency used, as well as the packet parameters. The packet is the fundamental unit created to transmit information, it is structured in API libraries using the packet XBee structure, in the figure 2.6 a diagram of the packet structure is presented, in this description it is possible to observe the complex-ity of the protocol, it is distributed in layers where different fields are defined in order to warranty a reliable and secure transmission.

Destination Start

API ID

DATA Delimiter

number

fragment Type ID

Source

ID Data

ID

ID Options

RF Data

Using the function SendXBee is possible send data

at low level.

ID

Check Sum LENGHT

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2.2 Operational Phase of a Positioning System

The procedure to obtain the actual position of a target is carried out by any positioning system in two stages, in the first stage recollection of interest data is realized; in the next stage integration and analysis of this data allow the estimation of the targets position.

2.2.1 Measure Phase

There are many variables that can be considered as possible options to determine the distance between two transceivers in RF Location awareness systems. Examining the different proposals (see details in table 1.1), there are five basic approaches:

Angle of Arrival AOA

This technique makes use of the anisotropic phenomenon in reception patterns of directional anten-nas (beam-forming) to estimate the angle of incidence at which signals arrive at the receiving sensor. The target position is then determined combining data about at least two reference points, to illustrate its principle of operation in figure 2.7 a representation of a location system with three elements is presented. In this scheme the position of base stations (A and B) is known as well as its incidence angles, then the target position (xcandyc) can be determined using the cosine rule.

The main concerns in this approach is the uncertainness nature of signal strength, which not only vary as a consequence of the use of anisotropic antennas, but it is also affected by variation of signal amplitude due mainly to features of transmission path and interference with other signals transmitted. RF positioning systems based on AOA techniques are supported, in most cases, by an specialized hardware that deal with the uncertainness of measurements by improving the antenna’s

direction-(Xb,Yb) B

A

C

Base Station A Base

Station B

Target

(Xc,Yc)

(Xa,Ya)

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2.2 Operational Phase of a Positioning System 21

ality [27,28] or by enhancing the infrastructure of the whole system [29]. However, there are other approaches based on radio interferometry [10,30] that obtain good results without many modifications on radio system (they will be discussed as part of the selection process in the next chapter).

Radio Signal Strength

the radio signal strength is a common parameter present in most radio transceivers, since every communication system has an Automatic Gain Control (AGC), which being part of the control loop is responsible for keeping the signal level in the demodulator invariable to sudden changes product of diffraction, reflection and scattering phenomena.

In order to accomplish this task, the AGC calculates the mean of the input signal (applying a low-pass filter over the input), and then, this result is compared with a predefined target level to set the new gain setting. Therefore, it is an indirect measure of the signal strength [31].

Since the radio signal strength is an standard measurement, a wide variety of approaches using this techniques have been developed. The general approach consists in recording and processing the signal strength of transmissions from multiples base stations, positioned in strategic places.

Examining relevant works (see table 1.1) it is possible to identify two categories, systems relying on the use of a propagation model and those supported by empirical measurements.

* Radio Propagation Method: Using Friis free space equation 1.1 it is possible to predict the

way in which the propagation of electromagnetic waves are attenuated. However, this model constitutes a naive simplification of the problem, since the propagation of waves is affected by reflection, diffraction and scattering.

Even thought the effects of propagation suffer from uncertainness mainly due to environmental conditions, an other model of propagation based on empirical evidence is accepted as a good estimator, it makes use of random variables to cope with these undesired effects [7,32]. That is,

Pr(d)[dBm] =Po(do)[dBm]₋10_∗np∗log[

d

(do)2d2

] +Xσ (2.1)

where Pr(d) andPo denote the received and reference power, d is the interest distance, do correspond to the reference distance,npis an empirical parameter that measure the rate at which

the RSS is attenuated and Xσ represents the random effect of shadowing and correspond to a

Gaussian distributed random variable with zero mean.

* Fingerprinting Method: This technique aims to construct an RSS profile of the coverage area. Based on the nature of electromagnetic propagation, which is highly influenced of the envi-ronment, unique patterns are identified by recording information about the radio signals as a function of the user’s location.

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This was one of the first techniques used, however, the constrains imposed by the off-line pro-cessing which involves a large memory space as well as a fast computation propro-cessing, delayed its use until nowadays where it has been used in combination with different probabilistic and estimation algorithms [33,34].

Times and Difference of Time Techniques

This techniques basically consists on measuring the time of flight of a signal using hardware or software solutions. In RF positioning systems the use of this technique is limited, the big constrain is the time of response of the devices, which has to be in the order of microseconds because the waves travel at the speed of light.

Different approaches have been proposed, for example, in 2008 an application under the ZigBee protocol was proposed, it uses temperature-compensated crystal oscillators [35] in order to get a proper response. However, few systems offer a feasible solution, this is the case of Pinpoint [5] which using a sophisticated protocol removes synchronization problems of conventional oscillators (see figure 2.8). In figure 2.8 the Pinpoint protocol is presented, it basically consists on keeping track of the time at which transmission and reception take place, therefore it operates under devices with a medium access control (MAC) clock stamping (conventional laptops) getting a reasonable accuracy (over 3 meters).

Time

ta1 ta2 ta4

tb1 tb2 tb3 tb4

Base Station A

Base _delay

delay Station B

delay ta3

Time

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Interference

Base Station B Unmodulated Carrier f1 Unmodulated Carrier f2

Station A Base

Base

Station C

RSS measured

RSS measured Mobile

Device

Figure 2.9: Interferometry Technique

Radio Interferometric

This technique constitutes the most recent way to measure the distance employing radio transceivers. This system was proposed six years ago in Vanderbilt University, it uses the Mica2 Berkeley motes to build a radio interference system. This devices thought, are simple and cheap, can be tunned at very low frequencies [36,37]. The basic idea is to produce a signal that can be easily measured with ordi-nary devices, therefore it is necessary to reduce the hight frequencies at which RF systems operate. To accomplish it, two unmodulated waves are generate and continuously transmitted by two base stations at very close frequencies (in the order of hertz). Once the waves collide, the composite signal will have a low frequency envelope easily detected by commonly available hardware (figure 2.9).

This technique has been used in two different system, one of them tries to estimate the local position of a sensor by comparing the phase and frequency of the interference signal measured in two different transceivers (figure 2.9) [11,36,37]. Another approach determines the angle of arrival of a signal combining the directionality of the antenna and the measure of a very differentiable signal, as it is the case of the interference wave generated due to the hight peaks of power emmitted, in figure 2.10 a basic scheme of the mobile device is shown.

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Interference Generated

3 XSM Motes

Figure 2.10: AOA Interferometer

2.2.2 Estimation Phase

Once data is recorded, it needs to be processed in order to eliminate discrepancies produced by the different sources of noise; and also to associate this information to a common framework. In position-ing systems there are many algorithms which integrate the information composition-ing from multiple inputs giving an estimate position, they can be classified as:

Trilateration

Trilateration is an analytical location method that uses distance measurements to identify the posi-tion of an object. As is shown in figure 2.11(a), the problem consists to find the intersecposi-tion between the range of three devices (in this case base stations) that in the ideal case represent a unique point therefore only one position, but in real environments the noise is unavoidable then the response is an area of possible location 2.11(b).

In order to attain a unique response, a common approach is to take multiple measures of this point and then calculate its mean value.

A

C

B

(a) Ideal Case

B

A C

(b) Error due to Noise Environ-ment

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Deterministic algorithms

These algorithms attempt to minimize an statistical distance, this mean they try to reduce the dis-tance between two statistical objects. Depending on the kind of object used it receives a different name, some of them are:

* Euclidean Metric: tries to minimize point to point samples, this is the common approach of

minimizing the error between calibration values and samples.

* Manhattan Distance: defines the minimum distance between two points as the sum of the

abso-lute differences of their coordinates.

* Mahalanobis distance: calculates the distance between two random vectors in the same distri-bution, it takes into account the correlations of the data set as another important factor to define if a point belongs or not to a set.

Probabilistic algorithms

These algorithms consider a degree of randomness as part of their logic, in general they try to model the uncertainness of a model as a probabilistic problem where the likelihood of a particular location is defined in the calibration phase which is considered as ana prioriconditional probability distribution. These algorithms have been used in some popular positioning system as is the case of EKAHAU which use Bayesian probability inferences to achieve a proper response.

Sophisticated algorithms

Another approach to find the actual position of a target is to use of another technique that tries to model this problem as a pattern recognition problem based on non-linear discriminant functions, this is the case of neural networks, a relative new approach that could eliminate discrepancies through a learning process.

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Chapter 3 Elements of the Proposed System

Any positioning system can be defined by its infrastructure and its operation mode, it refers to the way in which this systems determines local distances (between two motes) and estimates the global position of a target (by combining the information of different motes). At was illustrated in the last chapter, the evaluation of these features was an important step in order to delimit the problem, which by using general purpose hardware achieve feasible solutions.

In this chapter the selection of the different elements of the proposed system will be discussed, firstly, a feasibility analysis of the available hardware is presented, this important issue is a critical factor on the designing phase. Secondly, different operation modes will be evaluated and tested based on the hardware constrains. Finally, the complete system will be presented including each of the different proposed communication protocols needed to warranty a proper operation.

3.1 Hardware

Based on the features described in the last chapter, this technology has different benefits and also constrains. On the one hand, Waspmote devices have many support systems which can be easily integrate to the system, this modular platform promotes practical deployments where each device is specially designed by its particular purpose, but this functionality has the counterfeit effect of system’s latency and also the restrictions imposed by the API which control the access to configuration settings. On the other hand, Texas Instruments ez430-RF2500 devices offer simpler system where the user has a complete access to the platform, these devices can be programmed at low level using Assembly or C language. But the integration with additional software requires of new protocols (entirely designed by the user), also basics knowledge about the configuration and operation of this hardware is needed. These features make difficult the selection of one of these devices, further analysis will be done in order to make sure which of them is the best election for this particular application.

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28 Elements of the Proposed System

Signal Generator Gateway _PC

data Waspmote

Device

(a) Experiment’s Functional Diagram

PW

3

T

t

V

(b) Waveform Generated

transmition time

V

t

(c) Signal Recovered

Figure 3.1: Measuring Transmission Time on Waspmote Devices

3.1.1 Testing Time of Transmission and Reception Packets

One critical factor in a real time positioning systems is the latency associated to the estimation, time is the biggest constrain, so in order to select which platform could be useful, the delays on transmission and reception of packets was measured.

Waspmote Devices:

In order to measure the transmission time, a simple test was designed. Using one Waspmote board and gateway a remote sensing of an analog signal was built (figure 3.1(a)), the board basically was respon-sible of monitoring one of the analog input ports which was connected to a signal generator producing a rectangular pulse as is shown in figure 3.1(b). Once the process begins, each data is continuously transmitted, thus the analog wave is now uniformly sampled at the frequency of transmission, as is illustrated in figure 3.1(c).

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fre-3.1 Hardware 29

quencies were tested, the number of samples recovered by the gateway in each particular case and also an estimation of the sampling frequency are shown in table 3.1.

Frequency

Hz

Samples Recovered

Sampling Frequency

65 68.835

1.059 66 69.894

65 68.835

33 68.739

2.083 32 68.739

32 68.739

Table 3.1: Test results

ez430-RF2500 Development Tool

Tests done on this platform basically consisted on analyzing changes on current consumption in order to establish when a mote is executing some function, in this case transmission and reception of packets was studied.

Current consumption can be visualized by connecting a resistor between the board and batteries as is illustrated in figure 3.2. Two test were done, one of them aims to measure the latency produced by pure packet transmissions and the other one, studied delays on the complete demodulation process.

R

Target Board

Battery

Figure 3.2: Connection Diagram

In this test two boards were used; one of them was programed to detect when a packet is received (enabling the function MRFI-RxCompleteISR()) and the other one was continuously transmitting the same packet.

Using the battery board, the current consumption in those devices was measured, this process is detailed in figure 4.1, where is observed how the time employed to transmit or receive packets is in the same order (about 2.32ms), however the power consumption is different, due to the nature itself of this functions, being opposite processes, where modulation and demodulation of signals took place.

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(a) Transmission (b) Reception

Figure 3.3: Details of Current Consumption on ez430-RF2500

Technology Employed

Time is the most important concern to the development of a positioning system.The reliability and usefulness of this system depends on how this variable is controlled. Therefore, taken into a count that the Texas Instruments ez430 devices have hardware solutions instead of software solutions to do the management of packets and information (SPI serial communication), makes this platform faster and more reliable than the devices which although being a modular architecture, execute these func-tions through other devices as is the case of Waspmotes, Moreover, Waspmotes offer more tools and memory (it can be expanded to 2GB), the use of additional hardware add more latency in this system, as was illustrated on the test carried out, where the additional protocols make the process of sending packets too slow, it takes around 15ms to send one data byte, in comparison with the ez430-RF2500 modules which only need 2.32ms, which in this case compromise the whole system performance.

Considering that the purpose of this work is to build a localization system using an off-the-shelf sensor platform, the ez430-RF2500 development tool offers better features than the Waspmote devices. Because its highly integrability implies the use of few devices to accomplish each task, it simplifies the whole operation of the system doing the communication protocols more straight and also reducing the latency of this system which constitute a big concern for any real time positioning system.

3.2 Operational Phase - Measurement Parameters

The evaluation of positioning systems carried out in chapter 2, presented an overview of the different ways to use a radio frequency system as a sensor of distance. There are three basic approaches (time, signal strength or interferometry), each of them have an important number of purposes with different

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3.2 Operational Phase - Measurement Parameters 31

levels of accuracy. However, in most cases they have to be discarded because, they are not a feasible solution. In other cases further analysis have to be done in order to select the most useful tool.

3.2.1 TDOA Systems

In order to use the TDOA approach it is necessary has a system with advanced clocks or a software to compensate the side effect of inaccurate clocks. Examining different approaches using this technique, Pinpoint is a solution that seems to fit this system specifications, it uses common hardware (inaccurate clocks) to accomplish about three meters of error. However, this system needs devices with a medium access control clock stamping in order to get a response of microseconds in time-stamping, this critical feature is not present in platforms as TI ez430-RF2500 and Waspmote.

3.2.2 Interferometry

The primary requirements to use this approach is the hardware ability to generate unmodulated waves at really close frequencies. Evaluating the hardware available (TI ez430-RF2500 platforms), unmod-ulated waves can be generated with the CC2500 radio transceiver by configuring the mote to enabling OOK modulation and send an infinite packet of random values; but the transmitting frequency (carrier frequency) cannot be adjusted at level of hertz, the crystal used to generates the carrier frequency is af-fected by many issues such as capacitive loading errors, ageing and temperature. Hence these systems have an inherent drift (Xppm), which can be calculated by the next expression [38]

Error= fcarrier∗Xppm

106 (3.1)

Considering the transmitting range of these devices (2400MHz - 2485MHz), and the minimum crystal error (10ppm), the error oscillates between 24kHz-24.85kHz. These range of values are too hight to produce the desired interference in comparison to other works [36,37] which get a proper response by creating unmodulated waves with only a few hertz of difference (0.1Hz - 5Hz).

3.2.3 Radio Signal Strength Approach

The measurement of packet’s parameters by the communication system is also another option widely used in the literature. As was discussed in the last chapter, the radio signal strength is widely used in different applications, it is common to many communication systems and even it is part of popular protocols as the IEEE 802.12.4, which includes this information on the received packet. In figure 2.6, there are some features of the demodulation process accessible to the users (through STATUS-Registers) that could be useful.

Two elements of the structure RX-Metrics, are commonly used, they are the signal strength and the link quality indicator (RSSI and LQI, respectively). Although these localization systems are based

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on the signals strength, the link quality added more credibility to the measurea taken, this is because it is an indirect way to measure how pure is the received signal.

RSSI: The RSSI is the name as this parameter is known, it stands Received Signal Strength Indicator

and it is basically a measurement of the RF power received by the motes. In the Texas Instruments ez430-RF2500 devices, the RSSI is a digital value which can be read continuously from the RSSI status register. This value is continuously updating until a message is detected to be indexed to the packet received (this parameter is part of the RX-metrics).

LQI: The link quality indicator (LQI) is another important parameter common to many transceivers,

it is also a digital value which can be reader from the LQI status register, basically it is a measure of the quality of demodulation, it is obtained by comparing the constellation symbols with the expected (for minimum shift keying (MSK) demodulation it is a measured of the error in the carrier frequency). Therefore, if the input signal is strongly affected by noise, its LQI is low and zero when the input is only noise.

Sources of Error

Interference

The explosive growth of wireless technology leads to big changes in the portion of radio spectrum where industrial, scientific and medical devices work, this band known as 2.4GHz-ISM band has been overcrowded with a large number of devices (especially laptops which boots Wi-Fi technology) that vary not only in form but also in operation, each of them needs an specific support, hence, this band has an spread number of protocols such as IEEE 802.11, IEEE 802.15.4, ZigBee and Bluetooth coexisting together. Thus, interference in these kind of applications is an unavoidable issue, the figure 3.4(a) shows the seriousness of this matter, relating the signal strength with position and power of each foreign device.

The overlapping of the different standards in the ISM band forces to do a complete study of

the radio signal strength in which the TI ez430-RF2500 works (between 2.4GHz-2.485GHz) [39].

However, this analysis only takes into account the WLANs and Wi-Fi spectrum, due mainly to its power of transmission, which is enough to compromise the system proper operation.

An evaluation of this feature was done using InSSiDer 2.0, an open-source Wi-Fi scanning soft-ware that inspects networks tracking the strength of the received signal of each point detected, pro-viding not only the number of devices connected but also the channel occupancy. Different scenarios were measured and the multiple existing networks forced an examination of alternative frequency bands. Studying this spectrum, it was observed that Channel 14’s occupancy rate is almost null and this seems to be an standard, which can be justified if it is considered that Wi-Fi is regulated by each

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3.2 Operational Phase - Measurement Parameters 33

country and only a few countries enable the use of this channel, then most wireless devices are not designed to select it. As a consequence the system proposed in this thesis will be operating in this

band of frequencies (between 2,473GHz - 2484GHz) [40].

Antennas Issue

The TI ez430-RF2500 uses a surface mountable antenna that copes with the requirements of this platform, hence, small size, low cost and good performance are part of its features. It is basically a metal bar (Silver-Nickel-Tin alloy) printed on a rectangular ceramic base (9,5mm x 2,0mm) [41].

The main concern for this application is the radiation pattern of its antenna, which can be used to design the arrangement of transceivers, hence the antennas can be disposed to transmit and receive in the direction of its maximum transference of energy. The radiation pattern of the TI ez430-RF2500 is defined on the antenna’s datasheet [41] and it is presented in figures 3.4(a), 3.4(b) and 3.4(c). This antenna displays hight directionality over the yz plane, which is an indirect source of distorsion and errors on RSS measurements.

Analysing the description of the antennas gain, it seems necessary to take measures to counteract this undesired effect, a more isotropic radiation patter is necessary to warranty reliable measurement. In this work this issue leads to the use of two transceivers instead of one to measure the RSSI and LQI. Therefore, an arrangement back-to-back of two devices form the mobile unit of this system (localization target).

Design and implementation of a localization system based on a RF multipurpose platform