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A Positioning System for Indoor and Olos Environments
In some special cases, locations of wireless devices within buildings must be determined with reasonable accuracy. Consider the World Trade Center disaster on 9/11/2001. First Responders were spread throughout the World Trade Center without an effective means of command and control. Leaders had no way of knowing where individuals were and, hence, where to direct help. GPS is the most common method used to determine location, but GPS is largely ineffective within buildings due to multipath and obstructed line of site (OLOS) conditions. Another method for location determination uses time of arrival (TOA) measurements on communication signals transmitted from known locations. Three or more TOA measurements allow the receiver’s location to be estimated (trilateration). This method works best in flat, open environments; however, performance depreciates in OLOS environments such as inside buildings. In OLOS environments, signals propagate through multipath. This thesis investigates the location of wireless devices within building. The TOA error caused by multipath and OLOS conditions is modeled as a random variable with a probability distribution that is a weighted sum of a combination of Gaussian and exponential functions. Kalman filtering techniques are then used to mitigate the effects of TOA error and estimate the true location of the receiver. The results show that the position of a wireless device within a building can be accurately estimated.
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