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Wireless Position System

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Wireless Positioning System (WPS)

Index

Index. 2

1 . Introduction - “People Move. Networks must follow.” 3

1.1 Wireless Positioning System (WPS) . 3

2 . Position Determination 4

2.1 Calculation Methods 4

2.1.1 Trilateration 4

2.1.2 Fingerprint 5

2.2 Measure Methods 6

2.2.1 Cell of Origin (CoO) 6

2.2.2 Received Signal Strength Indicator (RSSI) 6

2.2.3 Time of Arrival (ToA) 7

3 . Projects 9

3.1 Magic Map . 9

3.2 Google 9

3.2.1 Demonstration 9

4 . Conclusion . 12

1                   Introduction - “People Move. Networks must follow.”[1]

Navigation belongs to our age. Outdoor navigation through the streets, jam diversion or a tracking device for a car, which reports the position in case of a theft or an accident. The technical advance let the market for services, based on position determination, grow. In most cases, GPS is used.

GPS is especially suited for outdoor navigation, because the satellites cover everything independent of the population density and determine the position accurate to 10 m. Certainly there are some other opportunities like Infrared or wireless networks.

1.1            Wireless Positioning System (WPS)

Wireless Positioning System is the location determination with the help of wireless networks. In times where almost everybody owns a wireless capable device (for example: notebooks or smartphones), WPS offers a big potential for position determination.

In the cities, there is a big density of wireless networks. Even the bigger companies have already extended their network by wireless components.
There is no need for additional or special hardware. The existing networks already offer the infrastructure, which needs to be changed in only very rare cases.

The position determination itself will be implemented by a software solution. So it’s a cheap way.
Even though WPS is in development, it’s possible to determine the position accurate to 3m (GPS reaches up to
10 m).

Because of the used low frequencies, which can soak buildings and matter, it promises a big potential for indoor position determination. GPS uses higher frequencies and can’t soak buildings, which makes it more difficult for indoor location. 
Additional, WPS offers a lot of possibilities for new services.

For example, navigation through a museum or a library with information of exhibits, forwarded directly to the mobile device, when it is nearly to the exhibit. For that, there a special routing protocols, which send packets to a physical position, not an IP address.

2                   Position Determination

2.1            Calculation Methods

Mostly, the position gets determinate by triangulation (determining by measuring angles), trilateration (determining by measuring distances), or by the fingerprint method. The techniques can be adjusted or used at the same time to get more precise results.
The necessary values can be measured by time of arrival, time difference of arrival or the signal strength. (Chapter 3.2)

The calculation can be realized on the client or on a remote server.

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On a server is an advantage of performance, but it could interfere the privacy.

2.1.1        Trilateration

Trilateration can be used for 2D and 3D localization. For 2D, there are two access points (or other known points), for 3D four, required.

The distance between the access point and the mobile device can be calculated by the signal strength or the time of arrival (Chapter 2.2.3). The distance will be used as a radius for a circular function of every AP. Equation of the circular functions gives the intersections of the circles.

The intersection of all circles shows the position of the mobile device. Calculating of distances is easier as angles and needs less technical effort. Therefore, trilateration is preferred over triangulation.


2.1.2        Fingerprint

The fingerprint method is based on a database of fingerprints. Every fingerprint is a map of different location based parameters. A location based parameter could be the received signal strength (Chapter 2.2.2) and the BSSID (ID of the Access point), of all available access points on one position.

The fingerprint is saved with the position in a database. This method needs specific knowledge of the environment, which changes constantly. The less the distance between the measure points the better is the accuracy of the position. A big advantage of this method is that there is no need for complex calculating on the server or the client.

It’s only a comparison. The measured fingerprint will be compared to the fingerprints in the database, and the match which fits best is the position. (It’s similar to the fingerprint comparison used by CSI)

Image 1 - Skyhook coverage of WLAN's in Perth[4]

Image 2 - Skyhook coverage of WLAN in Germany

2.2            Measure Methods

These are techniques to measure the needed variables for position determination / calculation.

2.2.1        Cell of Origin (CoO)

The cell of origin is the position of the connected access point. This is the easiest way for a rough position determination. So the position can limit to an area or a room. Location based services can be implemented with this method. The mobile provider O2, offered a service called homezone.

If the customer was connected to a specific cell, he didn’t pay for the calls. Another smaller example could be in a shopping center with some different shops. Every shop has its own AP. If the customer enters a shop, he gets the newest offers on his phone. Here is the strategy for the handover important.

2.2.2        Received Signal Strength Indicator (RSSI)

Additional to the cell of origin the relative received signal strength is measured. The signal strength depends on the distance between the client and the AP. The higher the RSSI the closer is the AP. The signal reduction and distance should be a logarithmical function.

So the distance can be estimated, if the output strength is known. But in the real world the waves are affected by environmental conditions (the air, all objects between sender and receiver, … ). So it’s difficult to forecast it.

The fingerprint method is the easiest way to use RSSI, because the environmental variable gets included.

This function shows the signal propagation in a building.

[5]
d= distance from the AP, PL = reduction of the signal, PL(d0) is a known reduction in a known distance. Xa is a variable which stands for the environmental interferences. But this is not possible to forecast, so it’s not possible to calculate the signal strength before.

Distance to Sender (m)

calculated

measured

Image 3 - Calculated & Measured Signal Strength in a Building[6]

2.2.3        Time of Arrival (ToA)

The distance between the sender and the receiver can be calculated by the time, the signal needs to arrive by the receiver. It’s a linear function with the radio propagation.

r=c*t
c= radio propagation speed - the speed of light (3x108 m/s)
t= time of arrival
r= distance between sender and receiver

In the case of WPS, the distances between sender and receiver, are a lot shorter than in GPS. That results that a clock difference between the receiver and the sender causes a big divergence of the distance. (1s = 300 m). So the clocks must be more precise and synchronized.

That is expensive and needs specific hardware. Alternatively to the synchronization, the sender can send two signals with a different radio propagation speed. With easy mathematic the divergence can be calculated and attended.

3                   Projects

There are some projects which are using WPS.

3.1            Magic Map

Magic Map is an open source solution, based on Java which is being developed at a German university. It uses WLAN, GSM, Bluetooth and RFID for determination. The calculation is a hybrid method of trilateration, triangulation and a radio map. The user can create an own map and connect to the offered server.

The focus lies on indoor localization. With three APs, the accuracy reached 3m.

3.2            Google

Google used street view to save all access points in a database. The database is updated by the clients automatically. Google uses it among other in Google Maps for clients without GPS.

Earlier, the user needed a plugin of Google to use that feature. Today, there is an interface implemented in the most browsers to use geolocation. This interface is defined by W3C[7]. It enables every website in the internet to locate the user (with the agreement of the user) using WPS.

3.2.1        Demonstration

The demonstration made with:

·        Firefox 6.02[8]

o       With Add-On: Live HTTP Header[9]

The bubble over the orange, little man enables the localization. The website triggers the location process in the browser. The browser asks the user's agreement for the position determination. After his acknowledgement the browser sends a request to a location database.

The database server is statically configured in the browser. It can’t be changed by the user. Firefox uses the server of Google, even so Chrome and Apple products. Internet Explorer uses a Microsoft server.

Image 4 - Browser ask for agreement of geolocation

The location appears in the map as a small circle with a radius. The client should be in the bigger circle. The position determination over WLAN is more precise than over LAN or GSM.

In the following Image is the HTTP Request from the browser to the location server. The format of the address request is JSON(defined in W3C geo location API specification). It contains all MAC Addresses, SSIDs, and signal strength of the access points, which the client can see.

Image 6 - HTTP Request Header with Access Points

4                   Conclusion

I think WPS has a big future. It will offer a big range of new useful services. Here and there is need for further development but it’s on a good way. And it’s already a rivalry of GPS. It will never replace it at all, but in some cases.

5                   References

[1] Aruba Networks Inc, “People move. Networks must follow”, 2008. [Online]. Available: [Accessed: Oct. 20, 2011]

[3] Google Inc. [Online]. Available: [Acessed: 20.10.2011].

[4] Skyhook Inc, “Coverage”. [Online]. Available: . [Accessed: 20.10.2011].

[5] A. M. Ladd, K. E. Berkis, A. Rudys, L. E. Kavraki, D. S. Wallach: „RoboticsBased Location Sensing Using Wireless Ethernet”, in Wireless Networks 11, Springer Science + Business Media Verlag, 2005, pp. 189-204

[6] Mathias Dalhaus, „WLAN Ortung innerhalb von Gebäuden mittels Signalstärkelinien“, Dortmund: aka 2006

[7] Andrei Popescu, „Geolocation API Specification”, w3.org, 2010. [Online]. Available: [Accessed: 20.10.2011]

[8] Mozilla Firefox. [Online]. Available: [Accessed: 20.10.2011]

[9] Add-On Live HTTP Header. [Online]. Available: . [Accessed: 20.10.2011]


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