wireless local positioning

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concept

remote positioning

self-positioning

indirect remote

Wireless Local Positioning -

Definition

measurement from remote site to mobile devicemeasurement from mobile unit to usually fixed

transponders (landmarks)

self%"tianine s ~ s l e m ith data transferof

Concepts, Solutions, ApplicationsMart in Vossiek, Lei f Wiebking, Peter Gulden, Ja n W i eghard t , C l emens Hof fma M

Siemens Corporate Technolog y, Otto-Hahn-Ring 6 ,81 73 0 Munich, Germany

E-mail: [email protected]

Absfrocf -Local positioning will be one of the most excitingfeatures of the next gen eration of wireless systems. 'With thistechnique a mobile device can either gath er the information aboutits position or can be localized from elsewhere. Completely newconcepts and features in wireless data transmission andtransponder systems will be enabled by this. Self organizingsensor networks, ubiquitous computing, location sensitive billing,context dependent information services, tracking and guiding are

only some of the numerous possible application areas. This papergives an overview over existing w ireless p ositioning solutions andattempts to structure different techniques and spplirations.

Furthermore two novel positioning systems currently developidby Siemens ar e featured as system examples. First B neuralcellular positioning system NCPS is introduced. This system isdesigned for positioning solutions for industrial, medical andconsumer scenarios and i s based on existing wireless voice or datainfrastruchwe. Second the Siemens local positioning radar (LPR)is presented. Th is system is designed for cm-precision and realtime

positioning in the area of industrial logistics, control and automa-tion. The application examples are completed by an application inthe field of augmented reality computing.

1. INTRODUCTION

In recent years an exponential growth o f wireless systems

has been observed. Wireless technology entered the realms of

consum er applications, as well as industrial, medical, logistics

along with m any other applications. Since wireless information

access is no w widely available th e dema nd for local positioningsystems draws significant attention [ I ] . This strongly emerging

need is driven by several aspects. At first the great success ofwireless systems is essentially explained hy the mobility theyenable. Mohility is by nature coupled with uncertainty. How-

ever, uncertainty is often not desired in applications like in-

dustrial manufacturing, network organization and many other

applications. Local positioning is the only mean to efficiently

overcome this uncertainty. Security and integrity also benefitstrongly from local positioning. Last but not least the data

capacity of wireless networks is inherently limited. Thus, an

intelligent context dependent information transfer is wanted.

One essential context is of course the location of the mobiledevice. This location dependent data transfer comes along with

very amactive novel services and convenience features.

Intense research activities are stimulated by this need.Nearly all 'big players' in the wireless world an d numerous

start-up companies are working on this topic an d consequentlythere is a growing number of commercially available wireless

local positioning systems.

A first distinction is made hetween self-positioning and re-

mote-positioning systems. In a self positioning system the

measuring unit is mobile. This unit receives the signals of sev-

eral transmitters in known location and has the capability to

calculate its actual position based on the measured signals.Remote-positioning systems work the other way round. Th eirsignal transmitter is mobile and several fixed measurement

units receive the transmitter's signal. In a master station the

results of all measurement units are collected and the trans-

mitters position is calculated. The major advantage of remote

positioning systems is that the mobile device can be small,cheap and power efficient. On the other hand this advantage is

paid for by the need for a complex system and backbone net-work and thus an expensive infrastructure. It severely depends

on the application if a remote-positioning or a self-positioning

system is better suited. Choosing the wrong approach can

increase the overall system cost by more than a factor of 10.This fact emphasizza that i t is hardly p ossible to build a single

system that cov ers a very broad applications range.

If a local positioning systems provides a wireless data link, itis of course possible to send the measurement result i) from a

self-positioning measurement unit to the remote side or ii) vice

versa. The first case i) can be thought of as indirect-remote-

positioning while case ii) is named indirect-self-positioning.

0-7803-7829-6/03/$17.000 2003 IEEE 219

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,

A . Measurementprinciples

Mainly three different measurement principles are used

today: Angle-of-anival (AOA), received signal strength (RSS),

and propag ation-time based system s that can furth er be divided

into three different subclasses: Time-of-arrival (TOA), round-

trip-time-of-flight (RTO F) and time-difference-of-arrival(TDOA). Figure 1 illustrates the foundation o f each conc ept.

MUU,

Figure 1: Measuring principles a) angle-of-arrival AOA, where RU and Mu

denote remofc and mobile unit, a! nd a, re the measured direction angles;

b) received signal strength RSS, where b and L? denote the measured path

loss e ) time-of-arrival U O A ) and roundnip time-of-flight (RTOF), w h m T,

and rl denote the measured one way or th e roundmp signal propagation time,

the spatial position is given by the intersection of circles centered at the RUa

d) time-difffrence-of-amval (TDOA), where AT12 and A n ) denote the

measured propagation time difference from a signal baveling fram the MU to

two differat RUs and the position is given by tbe intersecrim of hyperbolawith foci at the RUs.

In Ang le-of-arriva l (AOA ) systems the position is calcu-

lated via goniometry. With the use of directional antennas or

antenna arrays the angle or bearing relative to points located at

known positions is measured. The intersection of several meas-

ured direction pointers then yields the position value. The

accuracy of this approach is limited by the possible directivity

of the measu ring aperture, by shadowing and/or by multipath

reflections amving from misleading directions.

Received signal strength (RSS) systems are based onpropagation-loss equations. The free-space transmission loss

Le for instance is proportional to However, this simple

equation is in most cases unsuited to calculate the distance

value from the difference of transmitted and received power

under real conditions [3]. In indoor environments or built-upareas multipath fading and shadowing have a dominant effect

[4]. To overcome this problem advanced propagation models

are required or the actual field distribution in the area of inter-

est has to he leamt from measurements. Due to the highly non-

linear input-output mapping sophisticated algorithms or neural

networks are used. The latter approach is applied in the NCPSsystem described later on in this article. The major advantage

of RSS Systems is the fact that most modem radio modules

already provide a received signal strength indicator (RSSI).Also the bit error rate BER can he used to estimate the signal

attenuation. Consequently, implementing a local positioningsystem within a wireless commun ication system is more or less

a software topic and proprietary hardw are is not required.

Due to their physical restraints AOA and RSS systems only

deliver moderate position accuracy. The perhaps most intuitive

and accurate approach for local position measurement is to

measure the time-of-flight of the signal traveling from the

transmitter to the m easuring unit and hack. Obv iously the time-

of-flight can then be used to calculate the distance, Based on

several such measurements a 2D or 3D position can be derived

directly using lateralization. However, this straightforward ap-

proach has severe inherent difficulties when implemented.

Clock synchronization is a major issue. In fact, time-based

systems are mainly distinguished by the different concepts

dealing with this issue. In TOA systems the one-way propaga-

tion time is measured and the distance between measuring unitand signal transmitter is calculated. This concept requires

precise time synchronization of all involved fixed and mobile

units. In this case the absolute time synchronization must have

at least a precision related to the desired positioning accuracy.

For example a positioning error band of *I m requires an

absolute time synchronization significantly below 1 ns. Since

the clock information has to he distributed to and kept in the

mobile unit this approach either leads to a very expensive or

less accurate system. '

The absolute synchronization requirement can be replacedby a more moderate relative clock synchronization requirement

if an RTOF approach is chosen. Here the measuring unit moreor less acts as a common radar. A transponder responds to the

interrogating radar signal, and the complete round-trip

propagation time is measured. In this case the synchronisationchallenge is that the measuring unit has to know the exact

delaylprocessing time caused by the responder. A simple

example shows that this requirement is also difficult to meet.

Provided that both the measuring unit and the transponder havea fairly good X-tal clock source with 25 ppm accuracy a

processing time of I ms in the transponder can lead to a

measurement deviation of several meters. Hence, typically a

better clock synch ronization or a very short processing time are

required in RTOF systems. An elegant approach to avoid thissynchronisation problem is to use the concept of modulated

reflection [5,6] . Here the interrogating signal from the base

station is just reflected coherently superimposed with a specificmodulation. The main drawback of this approach is that the

radar signal has to travel the complete round-trip path. Hence

the propagation loss is proportional to at least the fou rth powerof the distance r. In consequence the standard form of thisapproach is only suited for sholt-range systems. However,

novel transponder concepts provide solutions to overcome thisdrawback [7,8]. Later on in this paper a very powerful RTOF

system based on modulated reflection is presented.

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\

Most of the available solutions today are remote TDOA

systems. In TDOA systems the time-difference o f arrival of thesignals received in several pairs of measuring units is evalu-

ated. The benefit over TDOA systems is that it is only neces-

sary to synchronise the measuring units. This synchronization

is done using a backbone network or a reference transpondkr in

a known position.Nearly all time-based local positioning systems are utilizing

signals and signal evaluation concepts that are well known

from modem radar systems. CW-signals, pulses or pseudo ran-

dom pulse-sequences, linear frequency modulated signals,

frequency hop or phase modulated signals can all be applied.

The different signal forms all have their specific pros and co ns

with respect to hardware / software burden, implementation,

and performance. There is one common characteristic for all

wideband modulation schemes: In multipath environmentsbandwidth is the key demand for precise positioning [Y]. Only

with an appropriate bandwidth it is possible to resolve and

separate multipath transmissions. Even with a bandwidth of

several 100 MHz, the accuracy of a well designed system will

be mainly limited by non-resolved multipath txansmissionan do r multipath fading.

111. SYSTEMS ANTJ SOLUTIONS

Figure 2 depicts a rough overview of current wireless local

positioning systems. It is beyond the scope of this paper to

provide a complete overview of systems available today. Only

some exem plary systems and companies are mentioned.

The hest known and most widely spread positioning systemis th e global positioning system GPS (or its differential Com-

plement DGPS) [IO]. This excellent and globally available

system is also well suited for many other outdoor local

positioning tasks. However GPS has its shortcomings in denseurban areas and inside buildings. Unfortunately this is exactly

the area where heavy, strongly-growing local wireless data

transfer takes place.

automation tracking. routingCO" 9, SIC.

I

'U0.1 0. 3 1 3 10 30 100 300 1K 3K

accwacy(meters)

Figllre 2: Overviewof current wiceless local positioning systems

several 10 km. TOA or TDOA measurements from neighboring

base sites can increase the accuracy to approx. 50 m to some

100 meters in urban areas.

Implementing local positioning solutions on standard

WLAN communication systems as DECT, WLAN802.11 or

Bluetooth is very attractive. Mutual synergy between the

positioning and the communication system is present. Some

years ago the Microsoft Research Group introduced their so

called RADAR system which is a RRS positioning systems

based on WLAN components [13]. TDOA solutions based on

DSSS or OFDM WLAN were reported by Li et al. [14].

Further on in this article the Siemens NCPS solution will he

described which is an RSS system either DECT or

WLAN802.11 based.

Intense activities with respect to local positioning can also

be observed in the Bluetooth community A local positioning

working group within the Bluetooth special interest group de-

fined the related standards (www.bluetooth.org). The

microcellular structure of a Bluetooth network allows to

localize a Bluetooth device very easily with an accuracy related

to the size of the piconet. To increase the accuracy the usualWLAN RSS evaluation concepts can be used.

The accuracy of typical WLAN positioning systems is ap -

prox. 3 to 30 m, with an update rate in the range of some sec-

onds. Some proprietary solutions such as the 3D-ID system

from PinPoint [ IS ] or the TDOA system from WhereNet [I61

have similar performance as the WLAN systems mentioned

above. However, the specially designed hardware and a proto-

col with longer power down periods allows for minimal power

consumption in the mobile devices and thus these productsmainly address the typical transponder market and not WLAN

data services.

As depicted in Figure 2 a technology barrier can be defined

between precision positioning systems that provide an accuracy

significantly better than Im and the less accurate systems. For

many tracking, routing and guiding applications a moderateaccuracy is sufficient. However, quite a few areas like

automation and control require much higher accuracy. Up tonow only proprietary broadband microwave systems can offer

this accuracy. Future Ultra Wideband (UWB) WLAN systems

will very likely be able to provide precise local positioning in-

formation. Several proprietary UW B local positioning systems

are already available today [17]. However, with the severe

power restrictions of the current FCC UW B regulation mainly

short range solutions are feasible.One of the most powerful wireless local positioning systems

available today has been developed by the Austrian CompanyABATEC [IS]. This system called LPM was especially de-

signed for sports applications. For less cost sensitive applica-tions it offers a wide range of more than 500 m, a high update

rate of less than 1 ms, and cm-precision. A similar update rateand accuracy is achieved hv the Siemens local positioning ra-

For cell phone positioning several different solutions exist

[2, 11 , 121. The easiest but most imp recise concept is to use the

cell-ID that is directly related to the physical position of the

serving site. Typical cell sizes vary from some 100 m up to

dar LPR that was recently launched for industrial applications

like crane and forklift positioning. This system was designed

under the guideline of minimal installation, infrastructure and

maintenance cost. The LPR will be described in detail below.

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A . RSS-System Example - Siemens NCPS

The basic foundations of RSS systems have already been

discussed. This section now introduces a specific RSS, the

SIEMENS neural cellular positioning system (NCPS). Specific

focus of the system is on cost reduction, achieved by using

existing wireless voice or data infrastructure, and avoiding theusage of a separate receiver.

Mobile handsets or wireless LAN adapters already scan the

radio band regularly to initiate a handover whenever the re-

ceived power drops below a certain threshold. The use of this

measurement data does not require additional hardware in the

receiver. Simply the received signal power together with the

base station ID is transmitted to the central position calculation

engine.Yet the main problem to overcome when using an amplitude

type quantity for indoor positioning is the complex non-linear

field distribution that turns the simple relation between

received power and distance into a complex mapping problem.

Figure 3 illustrates this situation .

The complexity of the field configuration is addressed byneural network learning m ethods. The actual distribution of the

electromagnetic field is learnt from measurements of thereceived power at known positions. The distribution is stored

on the central server, and serves as input for the positioncalculation engine. During localization the wireless device now

transmits the measured power for each of the base stations. The

position calculation engine then maps the position from the

field strength relative to each base station, and provides the

actual measured position. Typical system accuracy and pa-

rameters are summ arized in table 2. Th e specific advantages of

this system are the seamless integration into standard

communication systems, and that no additional hardware isrequired.

TABLE: h I C A L PARAMETERS OF NCPS-SYSTEM

Accuracy 15 - 15 [m ]

Coverage 1 100% inside cellular networkI LOS and NLOSI 2 - 5 secondsI DECT or WLAN 802.11

Acquisition speed

Infrastructure

B. RTOF -System Example - iemens LPR

As discussed before, several applications require accuracy of

a few cm , and oflen update rates below 100 ms. This can only

he met by proprietary microwave systems like the SIEMENS

Local Positioning Radar (LPR). In this RTOF system the

round-trip time-of-flight between a transponder unit and thebase station(s) is measured. An additional feature of the

SIEMENS LPR is that operation both as remote-positioning

and self-positioning system is possible. In the following mostly

the self-positioning operation as shown in Figure 4 is

considered.

-n n n n n n lFigure4; Operating principle and srmcNre of LPR in self-positioning mode

Based on the FMCW radar principle a mobile measuring

unit B, simultaneously measures the distance to all modulatedactive reflector units T,..T, in within reach. By solving the set

of triangulation equations based on the measurement geometry

and the measured distance values, the position of the mobile

unit is calculated. The basics of the measurement concepts

have been reported before [19]. The only differences of the

present solution are the different kind of modulated trans-

ponder and a more sophisticated radar front-end. These

changes lead to an extended m easuring range of several 100 m.

Furthermore the optimized system approach omits any ref-erence sources - neither clock synchronization nor a reference

unit are needed. Additionally, the current solution is fully real-

time capable, and update rates up to 1 !&z can be achieved. Ifthe measurement information is also needed in a central station

a standard WLAN link parallel to the LPR can be used. Table 3

summarizes the accuracy and performance obtained with the

current system.

TABLE: TWlCAL PARAMETERSOF LPR-SYSTEM

Accuracy

Coverage

I 0.05 - 0.15 [m ]I 100% inside transponder fieldI only LOS

Update time I 1-200 ms

InfraStmcture IProprietaly

IV. APPLICATIONS

A. User Localization and Asset Managemen!Infrastructure management is of great interest for smart of-

fices, hospital management and many o ther applications. Sys-

tems like the SIEMENS NCPS use the existing infrastructurelike cordless phones or WLAN systems, resulting in low sys-

tem and installation cost. Two different implementations of the

NCPS exist: The first is embedded in the Siemens HIPATH-

222



cordless telephony system, the second uses WLAN 802.1 I b

and WLAN 802.11g. Furthermore the desired area is usually

covered by the systems, avoiding additional installations.

A typical application is asset location within an office

building. The asset management software for instance sends a

localization request to find a color printer. The positioning

request arrives at the Location Server via LAN. The serverestablishes a connection to the wireless phoneifax unit of the

printer using a standard customer application protocol (CAP)

interface over the central switch. The information is relayed

hack and forth using the controller units (SLC) and the base

stations BS. The wireless phone performs the previously

described measurements and transmits the power measurement

data hack to the server. The sewer performs the processing,

calculates a position in standard global coordinates and finally

hands over the printer position to the application.

Th e NCPS system was tested in an office building. P in t the

field distribution of one floor w a s learned, and then a cordless

phone was located at several different positions. Figure 5

illustrates the topology of the building floor and displays the

measured positions. The resulting accuracy of a few meters is

sufficient for most infrasrmcture localization applications.

iccdigmh lPMislgih m * n r a Efciwsm"r 83nr

20 1 m m 1 1 3 C - ~ l o m a m n , W M g I ? M . S , d % m

~ M u r . B n a r y t m e h l s t ~ m 4 . 8 0 2 2

M m B - " w m mp" B Y 3

! M n m L m m ~ 1 0 - d ~ " : 2 . , ? s75'

j siumaddencbi:2opil

10 )

. ,Ob

40 -35 -30 -2s .m - l i -10 -5 0 5x I"?]

Figure 5: Obtained pasilions inside building

B. Intelligent Fa ct oq

The idea itself of an intelligent factory is based on knowing

the position of every production machinery, stock, and

transport means. Typically objects to he tracked are fork-lifts,

cranes, or maintenance workers. Stock can he tracked by

transmitting the precise position when being removed From the

transport vehicle. Figure 6 depicts a typical scenario.

Complete position tracking by the central computing station

enables several exciting new features:

a complete overview over the location and amount of all

supplies included in the manufacturing process

optimization of the material flowdefinition of virtual areas (storage area etc.),

restriction of operation of the transportation means

collision avoidance

Naturally this application requires a faster update rate,

adjusted to the speed of the transportation means. Furthermore

the precision of the position measuremen ts must be similar or

better than the physical dimension of the transported objects

The novel Siemens LPR was designed for such applications.

A very successkl exemplary application of LPR was the

localization of the indoor portal cranes of a steel-mill. The

building is an industrial hall with metal roof and walls, 50

meters wide and1000

meters long. Transponder units weremounted along the walls as RF-landmarks. The measuring unit

was installed on the crane, and computed its position using the

previously described algorithm. The position data was then

transmitted to the central computer, and processed by a

stockyard management system.

The field campaign yielded excellent results: Despite harsh

environmental conditions a maximal inaccuracy helow f 15 cm

was obtained. Figure 7a illustrates an exemplary measured

track of he crane. Figure 7b shows a histogram of a typical

positioning error distribution. In the test campaign the error

was m easured relative to a reference measurement system and

the depicted measurements were taken during the usualproduction process. The results are remarkable since the hall

had a typical RMS delay spread of several 100 ns the

maximum m easured values even reach I ps.The direct link with the stockyard management system

drastically improved material flow and turn around time.. The

outstanding performance shows that the system is well suited

for many other applications in logistics, automation and factory

supervision.

al b)

Figure 7 Histogram of measured distance error of LPR relative to referencesystem. 1000 Measurements dunng normalcrane operation inside rolling mill

223



C. AugmentedRenliw

Wireless local positioning is a key technology for novel u ser

context based services. Several applications are researched in

the SIEMENS-project INSTAR, jointly undertaken by Siemens

Corporate Technology, the JohaMes Kepler University Linz,

and the Ars Electronica Futurelab, Linz. One area of specificinterest is pedestrian navigation. A PDA serves a basic

computing platform and displays the augmented view. A

camera and an inertial sensor are rigidly attached to the PDA

such that the orientation of camera and display can be

measured reliably. Finally a positioning module must be pro-

vided, as for example a G PS-receiver for outdoor scenarios, or

an NCPS or LPR-system for indoor applications. The actual

navigation process, i.e. route calculation and map matching, is

performed on a remote server, which is accessed via wirelessLAN. Like this the entire positioning process could be inte-

grated into an autonomous mobile platform.

Figure 8 : lllustration of an AR-based runway maintenance system

An exemplary application is runway maintenance.

Conventional markers for defects like potholes are eitherhardly visible or distract pilots using the runmay. Additionally

they are d ifficult to find due to the scale and uniformity o f arunway. Using augmented reality in combination with local-

ization, a control team sends the position of the defects to the

server. The maintenance crew is then guided to the relevant

points using a mobile augmented reality system, avoiding the

complications o f purely map based navigation.

In the near future wireless local positioning technologies will

certainly he at the heart of a number of interesting new

augmented reality services, which in tum will provide the userwith a natural intu itive interface to abstract digital information.

V. CONCLUSION

Basic principles and exemplary solutions for modem wire-

less local positioning systems have been demonstrated, and aninsight into the huge application field of wireless localpositioning systems has been provided. Local positioning will

have a strong, lasting impact on the application of wirelesssystems and it will evoke paradigm changes in many areas.

That said it is obvious that a multi-billion dollar business is

emerging. Nearly all 'big players' in the wireless world and

nume rous start-up compa nies have intense research a ctivities in

this area. Some already claim to have somewhat basic IP and

universal, unique solutions. This contradicts the authors' point

of view who have not seen either a basic IP or a universal

solution. All available products today still address nichemarkets and proprietary systems are designed to meet theunique requirements of each application. In conclusion,

localization is an open field, and during the next years intensecompetition in this very attractive market is expected. A

welcome result of this competition will be that many powerful

and attractive wireless local positioning system s, solutions andservices become available.

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