performance analysis of localization techniques in wireless sensor

8/21/2019 Performance Analysis of Localization Techniques in Wireless Sensor

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PERFORMANCE ANALYSIS OF

LOCALIZATION TECHNIQUES IN WIRELESS SENSOR NETWORKS

BY

AARTI SINGH


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PRESENTATION OUTLINES

Introduction

Survey

Localization Techniques

Issues in Localization Algorithm Design

Problem Definition

References


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INTRODUCTION

WIRELESS SENSOR NETWORKS

a large number of self-sufficient nodes nodes have sensing capabilities

can perform simple computations

can communicate with each other.

APPLICATIONS

Health-care monitoring

In tele-monitoring of human

physiological data and drug

administration in hospitals.

Fig.2 health care

applications

Fig.1 sensor node


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Fig. 4 Military applications

• Environmental monitoring

measures light, temperature,

humidity

• Military Applications

In battlefield surveillances,

nuclear, biological and chemical

detection.

CONTINUED......

Fig.3 Environmental monitoring


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SURVEY

Self-localization capability is a highly desirable characteristic

of wireless sensor networks. In environmental monitoringapplications such as bush fire surveillance, water quality

monitoring and precision agriculture, the measurement data

are meaningless without knowing the location from where the

data are obtained. A novel localization scheme, is proposed, called ALRD (AoA

Localization with RSSI Differences), to estimate AoA for

localization in 0.1 second by comparing the RSSI values of

beacon signals received from two perpendicular-orientationdirectional antennas installed at the same place.


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CONTINUED.......

A new algorithm, adaptively weighted centroid localization

(AWCL), is proposed.

1. Firstly a more reasonable path loss exponent is

adaptively estimated according to the surroundings where

the target nodes situates.

2. Secondly the target position will be calculated by usingthe weighted centroid method in which exponents

estimated in the first stage are adopted.

Time Difference of Arrival (TDoA) algorithm is proposed .


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WHAT IS LOCALIZATION?

Localization is the process for determining the absolute orrelative physical location of a specific node or the target

node. Localization techniues can be classified into

Range free vs Range based Centralized vs Distributed

Anchor free vs Anchor based


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Range free vs Range based

Range free use local and hop-counting techniques while

range based use AOA, TOA etc method.

Centralized vs Distributed

In centralized all computation is done in a central server. In

distributed Computation is distributed among the nodes

Anchor free vs Anchor based

Anchor nodes that know their coordinates a priori.

Anchor free nodes use relative coordinates. While anchorbased use nodes to calculate global coordinates.


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RANGE FREE VS RANGE BASED

In range-free schemes, the sensor node location is

estimated merely according to network connectivity. Suchschemes need no extra hardware; however, their accuracy

is not good enough and they usually rely on deploying a

large number of beacon nodes to improve the accuracy.

Range-based schemes usually have better accuracy. Theymeasure

the time of arrival (ToA)

time difference of arrival (TDoA)

angle of arrival (AoA)

received signal strength indicator (RSSI)


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LOCALIZATION TECHNIQUES

TIME OF ARRIVAL (ToA)

Time of Arrival (ToA) algorithm bases on signal delay. In time of arrival (ToA) technique the distance is estimated

by calculating propagation time of signal betweentransmitter and receiver .

It can be one way propagation time or two way propagationtime.

In one way propagation, the time taken by the signal fromtransmitter and the receiver is calculated and then distanceis estimated by using:

S = vxtWhere, v = velocity of the signal

t = propagation time

S = measured distance.


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CONTINUED.......

In case of two-way ranging, the time taken from

transmitter to receiver and back to transmitter is calculatedand then distance is estimated by using:

S = v x (t x ½ - t reply)

Where, t reply = processing time taken the receiver to emitout RF signal back to the transmitter


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TIME DIFFERENCE OF ARRIVAL (TDOA)

TDoA is based on multilateration navigation system.

In TDOA three anchor nodes used for localizing. The unknown

node transmit three pulses to three nodes (anchor) which are

spatially separated.

TDoA technique based on ultrasound needs the auxiliary

ultrasound transceiver that adds to the cost and size of the

platform, and also has the weakness of limited range and

directionality constraints.

It cannot be applied to large-scale networks.


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CONTINUED.......

TDOA is based on

1) The difference in the times at which a single signal from asingle node arrives at three or more nodes

2) The difference in the times at which multiple signals from a

single node arrive at another node

Advantages of TDoA

low-cost and high precision

requires the time-consuming movement of anchor and

cannot achieve rapid positioning.


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ANGLE OF ARRIVAL(AOA) AOA is defined as the angle between the propagation

direction of an incident wave and some reference direction,which is known as orientation.

Orientation, defined as a fixed direction against which the AOAs are measured, is represented in degrees in aclockwise direction from the North. When the orientation is or

pointing to the North, the AOA is absolute, otherwise, relative. This technique is based on angular estimation for localization

rather than distance or time.

Ultra wide band (UWB) is a mode of wireless communication

in which minimum bandwidth should be at least 500 MHz ormore.

There are two types of UWB transceivers impulse radio andmultiband.

0


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CONTINUED......

UWB transceivers operate at a very low power which issuitable for applications where power is constraint such asbattery operated devices .

In fig.5 transmitter P in position (x ,y) sends a signal.Directional antennas in points (x1, y1) and (x2, y2) detectangles α 1 and α 2 . Intersection of lines described by known

points and angles determines where transmitter P lies.

Fig.5 Localization using AoA algorithm


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CONTINUED....... If we have three known points A(x1,y1), B(x2,y2),C(x3,y3)

and we know that point P(x,y) is distant d1, d2 , d3 from

these points respectively,hence x and y can be find havingtwo exceptions.

1. First when at least two known points have the sameposition in fig 6.

fig.6 Finding point’s position knowing distance to three

known points


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CONTINUED.......

2. Second when all three points A, B and C lies in one line

in fig 7.

Fig.7 When known points A, B and C lie in line point P cannot

be determined uniquely.


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CONTINUED......

Advantages of AoA

First since the phase of the received signal is usually morestable than the received signal strength (RSS), AOA

estimation can achieve higher accuracy than RSS-based

localization approaches.

Second, given an effective AOA estimation scheme, twoantenna arrays suffice to achieve accurate target

localization, while range based approaches require three or

more sensor nodes.


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RECIEVED SIGNAL STRENGTH(RSSI)

RSSI range based localization algorithm is a simple and cost

effective localization technique that relies on measuring theRSSI for distance estimation.

RSSI is a unitless metric used to measure the power of the

received radio signal.

It is represented by one-byte integer and can assume any

value in the range 0 to 255.

The free space propagation model is used to predict

received signal strength when the transmitter and receiver

have a clear, unobstructed line of sight path between them.


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CONTINUED.....

This free space power received by a receiver antenna which

is separated from a transmitter antenna by a distance d, is

given by the free space equation

Pr (d) =2

2 2(4 )

t t r PG G

d L

where Pt = transmitted power

Pr (d) = received power which is a function of the T-R

Separation

Gt = transmitter antenna gain

Gr = receiver antenna gain

d = T-R separation distance in meters

L = system loss factor not related to propagation

= wavelength in meters.


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CONTINUED......

The two-ray ground bounce model is a useful propagation

model that is based on geometric optics, and considers boththe direct path and a ground reflected propagation path

between transmitter and receiver. This model has been

found to be reasonably accurate for predicting the signal

strength, it can be expressed as

Pr (d) =

Where

ht = height of the transmitterhr = height of the reciever

2 2

4

t r

t t r

h h PG G

d L


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ISSUES IN LOCLIZATION ALGORITHM DESIGN

ISSUES

RESOURCECONSTRAINTS

NONCONVEXTOPOLOGIES

ENVIRONMENTALOBSTACLES AND

TERRAINIRREGULARITIES

NODE DENSITY


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ISSUES IN DESIGNING LOCALIZATION ALGORITHM

RESOURCE CONSTRAINTS:

Sensor networks are typically quite resource-starved and

battery powered i.e communication, processing, and

sensing actions are all expensive, since they actively

reduce the lifespan of the node performing them.

NODE DENSITY:

Many localization algorithms are sensitive to node density.For instance, hop count-based schemes generally require

high node density so that the hop count approximation for

distance is accurate.


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CONTINUED.......

NONCONVEX TOPOLOGIES:

Localization algorithms often have trouble in positioningnodes near the edges of a sensor field. Sensors outside themain convex body of the network can often proveunlocalizable.

ENVIRONMENTAL OBSTACLES AND TERRAINIRREGULARITIES:

Environmental obstacles and terrain irregularities can alsowreak havoc on localization. Large rocks can occlude line ofsight, preventing TDoA ranging, or interfere with radios,introducing error into RSSI ranges and producing incorrecthop-count ranges.


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PROBLEM DEFINITION

Localization techniques both range free and range based

are totally based on very fine numerical computation of

various properties of wave like range (transmission),

shape (propagation), power (transmitted/received), time(sending/arrival) etc. These parameters of wave are very

much sensitive towards the environmental situation and

presence of environmental obstacles.


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OBJECTIVES OF MY DISSERTATION:

The impact of environmental conditions such as presence of

obstacles in the propagation path, phenomena of reflection

etc on the localization techniques can be analyzed in terms

of percentage error in sensor location computation.

Mathematical model for location estimation in shadowing

environment will be proposed.

Comparative study among existing localization techniques in

the presence of environmental conditions will also be one of

the main part of my objectives.

The proposed model will be simulated in network simulator

ns-2/Matlab.


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REFERENCES[1]. A. J. Goldsmith and S. B. Wicker, “Design challenges for energy constrained

adhoc wireless networks”, IEEE Wireless Communications , vol. 9 , no. 4 , Aug.2002 , pp. 8 – 27.

[2]. R. Atanassov, P. Bose, M. Couture, A. Maheshwari, P. Morin, and M. Paquette,“Alogorithm for optimal outlier removal,” Journal of Discrete Algorithms, Vol. 7,Issue 2, pp.237-248, 2009.

[3]. Z. Chaczko, R. Klempous , J. Nikodem, M. Nikodem, J. Rozenblit, AnImprovement of Energy Aware Routing in Wireless Sensors Network , EuropeanModeling and Simulation Symposium, Barcelona, Oct 2006.

[4]. Guowei Shen, Rudolf Zetik, Ole Hirsch, and Reiner S. Thomä; “Range-BasedLocalization for UWB Sensor Networks in Realistic Environments” in proceedingsof EURASIP Journal of Wireless Communication & Networking-Special Issue ontheoretical & Algorithmic foundations of wireless ad hoc & wireless sensornetworks-2010.

[5]. Gouging Maoab, Bares Fidan, Brian D.O. Anderson “Wireless sensor

network localization techniques” in proceedings of Computer Networks: TheInternational Journal of Computer & Telecommunication ACM 2007.


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CONTINUED......

[6] . T. S. Rappaport, Wireless communications: principles and practice 2nd Edition: Prentice Hall PTR New Jersey, 2002.

[7]. Ivan Stojmenovic, University of Ottawa; Handbook of Sensor Networks, ALGORITHMS AND ARCHITECTURES.

[8]. C. H. Our “A Localization Scheme for Wireless Sensor Networks UsingMobile Anchors With Direction l A e s ” IEEE Sensors Jour l Vol. 11, No. 7,pp. 1607-1616, 2011.

[9]. Jehn-Ruey Jiang, Chih-Ming Lin, “ALRD: AoA Localization with RSSIDifferences of Directional Antennasfor Wireless Sensor Networks”

International Conference on Information Society ( i-Society 2012).

[10]. Yanjun Chen, Quan Pan “AWCL:Adaptive Weighted Centroid TargetLocalization Algorithm Based on RSSI in WSN” IEEE Sensor jour1,pp 978-1-4244, 2010.


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THANK YOU

performance analysis of localization techniques in wireless sensor

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