Positioning systems enable location-awareness for mobile computers in ubiquitous and pervasive wireless computing. By utilizing location information, location-aware computers can render location-based services possible for mobile users.
Indoor positioning systems based on location fingerprints of wireless local area networks have been suggested as a viable solution where the global positioning system does not work well. Instead of depending on accurate estimations of angle or distance in order to derive the location with geometry, the fingerprinting technique associates location-dependent characteristics such as received signal strength to a location and uses these characteristics to infer the location.
The advantage of this technique is that it is simple to deploy with no specialized hardware required at the mobile station except the wireless network interface card. Any existing wireless local area network infrastructure can be reused for this kind of positioning system.
While empirical results and performance studies of such positioning systems are presented in the literature, analytical models that can be used as a framework for efficiently designing the positioning systems are not available. This project develops an analytical model as a design tool and recommends a design guideline for such positioning systems in order to expedite the deployment process.
A system designer can use this framework to strike a balance between the accuracy, the precision, the location granularity, the number of access points, and the location spacing. A systematic study is used to analyze the location fingerprint and discover its unique properties. The location fingerprint based on the received signal strength is investigated. Both deterministic and probabilistic approaches of location fingerprint representations are considered.
The main objectives of this work are to predict the performance of such systems using a suitable model and perform sensitivity analyses that are useful for selecting proper system parameters such as number of access points and minimum spacing between any two different locations.
Source: University of Pittsburgh
Author: Kamol Kaemarungsi