WLAN-based Indoor Navigation. What are the new technical possibilities?

Content

1 Introduction... 1
1.1 Motivation... 1
1.2 Aim of the work.... 1
1.3 Delimitation of the research topic... 2

2 Definition of important terms... 2

3 Current state of practice... 3
3.1 Sensor-supported WLAN-based technology... 3
3.2 The fields of application... 6

4 Conclusion... 7

5 References... 8

1 Introduction

1.1 Motivation

Due to the rapid development of mobile devices, especially regarding their performance, the possibilities of navigation with these devices are increasing. Especially, when it comes to indoor navigation, there is still a lot of potential. The problem is that the GPS signal is not available inside buildings and therefore navigation is not possible with normal applications as these no longer receive a signal from the satellites and thus the position of the mobile device can no longer be determined.[1] For this problem, the technical variants of indoor navigation are used which will be explained in this paper. However, the possibilities of indoor navigation also have their downfalls. Many technologies have a high acquisition value since the map material must be made available first and usually has to be digitized first. In many areas, the technology must first be retrofitted to achieve the desired performance. The accuracy of the position determination also plays a role. Therefore, it is important that the technology can guarantee high accuracy when it comes to calculating the position.[2]

The topic is of particular relevance to us because these technologies have great potential and enable seamless navigation inside buildings. Especially, the multitude of possibilities makes the topic interesting and it is important to determine which of these technical possibilities is really suitable for use and will be so interesting for the user.

The paper is intended to give the reader an overview of WLAN-based indoor navigation. In addition, it shows that such navigation is already possible within buildings, and it also addresses remaining obstacles.[3]

1.2 Aim of the work

The main purpose of this paper is to study WLAN-based indoor navigation. It is to be clarified which technical possibilities exist in indoor navigation and how these can be improved to provide even more precise navigation in buildings. Furthermore, this paper outlines with the possibilities of the current state of the art.

1.3 Delimitation of the research topic

This topic deals exclusively with the possibilities of indoor navigation and the accurate determination of a position, sothat an exact navigation is possible. Passive possibilities such as navigation with RFID chips are also left out as these technologies have high acquisition costs.

We will go into WLAN-supported navigation with fingerprint technology as it has low acquisition costs compared to other possibilities. WLAN is also widely used, especially in shopping centers and airports, and thus, provides a high density of signaling devices for precise location determination.

2 Definition of important terms

Indoor navigation is used to determine the location within buildings where no GPS signal is available. Determining one's position means determining one's own position. This location is used for the rest of the navigation process and is an important component, therefore, it is updated at regular intervals to allow accurate navigation.[4]

The fingerprinting method used for WLAN localization serves to determine the position of the user and their mobile device. Fingerprints of the signal strength of the received WLAN router, here the BSSI values, are stored in a database. These are called up later during navigation and the location can be determined based on the different signal strengths. This method is called fingerprint because each constellation of the different signal states like a fingerprint is only present once.[5]

Gyroscope sensors and acceleration sensors in a smartphone are used to calculate the acceleration and orientation of the mobile phone user. The gyroscope sensors measure the rotation of the mobile phone with the aid of gravity to detect acceleration, rotation, and changes in position. The results are used for further calculations in the navigation process.[6]

The algorithms in this thesis serve to calculate the shortest path. The nature of humans is that they always want to take the shortest route and do not like to take detours. The calculation of the path success in most cases according to the algorithm of Dijkstra as this always calculates the most optimal route.[7]

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[1] Cf. Obermaier, J. (2011), p. 2

[2] Cf. Obermaier, J. (2011), p. 3

[3] Cf. Gleim, D. (2012), p. 2

[4] Cf. Oschatz, A. (2011), p. 6

[5] Cf. Oschatz, A. (2011), p. 13; Cf. Teker, U. (2005), p. 91

[6] Cf. DATACOM book publisher (2014)

[7] Cf. Schwanengel, A. (2010), p. 45