Relative Accuracy based Location Estimation in Wireless Ad Hoc Sensor Networks

May Wong1 Demet Aksoy2

1Intel, Inc. 2University of California, Davis

ICC 2007

Outline

Introduction Related Work QUAD ( Quadrant-Based estimation)

Localization algorithm Performance evaluation Conclusions

Introduction

In WSNs, Sensors are used in a wide range of

applications. Ex. scientific research, military, healthcare, and

environmental monitoring. Every user has to depend on the location

provided by the sensor to analyze observations Location information is important for data

analysis.

Introduction Sensor are not known where were they deployed. There are two ways to get sensor’s position by

themselves. Equip GPS.

High Cost, Big size and power consumption Localization algorithm .

Location errors are inevitable in estimations. The precise location of each sensor is not

necessary in most sensor network applications.

Introduction

AB

Observer Considers that pollution is from B to A.

B’A’

Introduction

AB

B’’A’’

Observer Considers that pollution is from A to B, but real condition is from B to A.

Introduction

Motivation Reduce hardware cost. Previous work in localization focus on

individual accuracy position. Goal

Minimal Specialized Hardware Eliminate error relative location. Robustness to Network Density.

Related Work

A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6

A(x1,y1)

B(x2,y2)

C(x3,y3)

X

(C,(Xc,Yc), Hop Count)

Reference Node

Unlocalized Node

Localized Node

Related Work

X

Reference Node

Unlocalized Node

Localized Node

50m60m

100mA(x1,y1)

B(x2,y2)

C(x3,y3)

m 2035

60100

m 18.3333

6050

m 18.7553

10050

Hop

Hop

Hop

DistC

DistB

DistAA,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6

Related Work

DV-Hop could not estimate a position.

Quad Localization algorithm

Phase1 Hop distance dissemination

DV Based

Phase2 Position vote

Determine sensor relative location

Phase3 Location estimation

Determine location

Quad Localization algorithm

Hop distance dissemination

A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6

V(x1,y1)

U(x2,y2)

T(x3,y3)

A

(C,(Xc,Yc), Hop Count)

Quad Localization algorithm

Position vote

A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6

V(x1,y1)

U(x2,y2)

T(x3,y3)

A

(C,(Xc,Yc), Hop Count)Near Set: AFar Set: B,C

Quad Localization algorithm

Location estimation

Ｂ Ｃ

Ａ

W

Z

Y

(49,49)

(50,48)(50,48)

(50,50)

Near Set Y,(50,50),3Far Set

W,(49,49),5Z,(50,48),5

Near Set W,(49,49),1Far Set Y,(50,50),3 Z,(50,48),3

N

W

North

South

North

South

Performance evaluation

Simulator is implemented by C++ Radio range 5 unit 100 x 100 grid size Random number of nodes Different topology

Performance evaluation Smooth

(1) Hop by hop gradient propagation to get estimated distance to reference node.

(2) Local computation by each node using multilateration procedure.

Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network. In Proc. 2nd Intl. Workshop on Information Processing in Sensor Networks (IPSN)

b

c

a

a a

Performance evaluation DV-Hop Min-Max : corrections are done by local averagi

ng

The n-Hop Multilateration Primitive for Node Localization Problems (ACM) Mobile Networks and Applications 03

b+c b+c

X

Y

V

Set the center of the bounding box as the estimate.

Performance evaluation

Performance evaluation

X Coordinate Estimates using DV-Hop

Performance evaluation

X-Coordinate Estimates using Min-Max

Performance evaluation

X Coordinate Estimates using QUAD

Conclusions

In this paper, they use coordinate and relative position to estimate

location. provide a accuracy topology.

Thank You!