TPS: A Time-Based Positioning Scheme for outdoor Wireless

Sensor Networks

Authors: Xiuzhen Cheng, Andrew Thaeler, Guoliang Xue, Dechang ChenFrom IEEE INFOCOM 2004

Outline

Introduction Overview of Location Detection

Techniques

Outline

Introduction– The challenge of Location Discovery– Overview of TPS

The challenge of Location Discovery

The algorithm must be distributed and localized ( scalable ).

The protocol must has low communication and computation overhead

The positioning functionality should not increase the cost and complexity of the sensor

The location detection scheme must be robust. TPS proposed in this research is designed to meet

these challenges.

Overview of Location detection Scheme

Two phase of major current sensor location detection schemes :

1. Range or angle measurement

2. Calculations Some schemes perform a refinement

phase

Types of Existing Approaches

Time based methods– Time-of-Arrival (ToA)– Time-Difference-of-Arrival (TDoA)

Received-Signal-Strength-Indicator (RSSI) Angle-of-Arrival (AoA) Range estimation use network connectivity

– DV-hop– DV-distance– Euclidean

ToA (Time-of-Arrival)

Processing delays and non-LOS propagation can introduce errors

Requires synchronization to accurately measure time-of-flight.

TDoA (Time-Difference-of-Arrival)

RSSI (Received-Signal-Strength-Indicator)

Computes distance based on transmitted and received power levels and a radio propagation model.

RSSI is mainly used with RF signals. Due to multipath fading ,RSSI can be

inaccurate .

AoA (Angle-of-Arrival)

The calculations of triangulation is simple. It’s difficult to measure accurately when a

sensor is surrounded by scattering objects

Sensors or BS should equip with directive antennas or antennae arrays, which may be prohibitive due to cost and form factors.

Overview of TPS

Based on TDoA (Time-Difference-of-Arrival) of RF signals measured locally at a sensor to detect range differences from the sensor to 3 BSs.

These range differences are averaged over multiple beacon intervals before they are combined to estimate the sensor location through trilateration.

Overview of TPS

Not iterative Refine position estimates by averaging

time difference measurements prior to calculating position.– This averaging requires less

computation than repeatedly solving linear system matrices, least squares or multilateration algorithms.

Using network connectivity

If a sensor can not receive signals from enough BSs,– ≥ 2 for AoA– ≥ 3 for ToA, TDoA, and RSSI

none of the previous techniques will work. Network connectivity can be used for

range estimation

DV-hop

BSs flood their positions to all nodes in the network.

Sensors compute the minimum distance in hops to several base stations.

BSs compute an average distance per hop to other BSs.

BSs then flood this information to the whole network allowing nodes to calculate their positions.

Example of DV-hop

L1 computes the correction (estimated average size of one hop) (100+40)/(6+2) = 17.5

2 hops6 hops

DV-distance

DV-distance replaces hop counts with cumulative range estimates in meters estimated from RSSI.

AHLoS

A TDoA based scheme BSs transmit both ultrasound and RF signals

simultaneously. The RF signal is used for synchronization purposes. A sensor will measure the difference of the arrival

times between the two signals and determine the range to the base station.

Multilateration is applied to combine range estimates to generate location data.

AHLoS provides fine-grained localization capability.

Ultrasound transceivers can only cover a short range (several meters)

large numbers of base stations may be required to cover large areas.

Multilateration

Advantages of TPS

Offers scalability - Sensors independently compute their positions.

Requires no time synchronization - using a local clock

Sensors do require the ability to measure the difference in signal arrival times with precision– No requirements for an ultrasound receiver,

second radio or specialized antennae at BS or sensors.

Advantages of TPS

The computation overhead is low– Multilateration based systems require matrix

operations to optimize the objective functions No communication overhead

– Sensors listen passively and make no radio transmissions.

– BS transmit all the beacon signals. – This conserves sensor energy and reduces RF

channel use.