Indoor Localization

Indoor Localization

The demand for tracking people or objects by using a precise geographic location information is steadily increasing especially for location based services e.g. guide visitors in exhibitions. Satellite navigation systems like the Global Positioning System (GPS) work effectively and accurately in outdoor environments, where the GPS receiver estimates its current position by performing different ranging measurements from at least four satellites. In an outdoor environment the effect of multipath is very low and the receiver has most of the time Line-Of-Sight (LOS) to a sufficient amount of satellites. The satellite signals are usually not influenced by obstacles. A big problem is that GPS works very poorly in indoor environments due to the shielding and obstruction of satellite signals. Therefore GPS is unavailable and unsuitable for an indoor environment. A possible technology to solve this big issue is the commonly used Wireless Local Area Network (WLAN). WLANs have the big advantage of being widely spread in numerous of indoor environments and installed in a big concentration. Moreover existing WLAN systems such as 802.11n, which uses multiple antennas (MIMO), make the realization of network-based indoor positioning possible by using different measurement techniques. These measurements can help to determine the current user positon by analyzing the signal delay, signal strength and phase difference of the radio frequency signals. However the major source of error for these types of indoor localization techniques are related to the characteristic signal propagation phenomena. These phenomena, which influence the signal propagation in a dense multipath environment (e.g. building) are reflections, absorption, fading etc. A simulated channel impulse response (CIR) of an indoor environment is depicted below.

Different signal parameter estimation algorithms have been developed to deal with channel impulse responses of indoor environments. Each of these algorithms has its own benefits and difficulties which strongly depend on the current environment. The Center for Mobile and Wireless Communications (MOWICOM) focuses its research on creating an adaptive algorithm, which chooses the best estimation algorithm for the current environment. As channel estimation is typically implemented in WLAN systems in order to perform the channel equalization, this estimation technique can be used to extract typical parameters for analyzing the current environment and to select and combine the suited localization algorithms. Therefore a superior performance can be expected from this approach.

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Michael Kuhn

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64295 Darmstadt
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+49.6151.16-38249
Michael Kuhn