THESIS
2014
xi, 45 pages : illustrations ; 30 cm
Abstract
Many fingerprint-based techniques have been proposed and studied in recent years for indoor
localization. As wireless signals may change overtime or suddenly (due to addition/removal of
APs, construction/tear-down of partitions, adjustment of AP powers, etc.), the fingerprint database
needs to be updated regularly and frequently in order to achieve high localization accuracy. Traditionally the site is surveyed to collect the new radio signatures by means of trained surveyors or crowdsourcing. However, these approaches are not satisfactory due to their laborious or intrusive nature.
We propose Chameleon, a novel survey-free technique to maintain an updated fingerprint database which is adaptive to signal changes. Chameleon eliminates the need of any surveyors or explicit user partici...[
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Many fingerprint-based techniques have been proposed and studied in recent years for indoor
localization. As wireless signals may change overtime or suddenly (due to addition/removal of
APs, construction/tear-down of partitions, adjustment of AP powers, etc.), the fingerprint database
needs to be updated regularly and frequently in order to achieve high localization accuracy. Traditionally the site is surveyed to collect the new radio signatures by means of trained surveyors or crowdsourcing. However, these approaches are not satisfactory due to their laborious or intrusive nature.
We propose Chameleon, a novel survey-free technique to maintain an updated fingerprint database which is adaptive to signal changes. Chameleon eliminates the need of any surveyors or explicit user participation by making use of the signals measured by the clients, thereby making clients as surveyors as well. Independent of any fingerprint-based localization algorithm, it employs an efficient algorithm to filter out the altered AP (access point) signals to achieve highly accurate indoor localization. Using the calculated location and the measured signals, the radio map in the
database can be continuously updated without manual intervention. Both extensive simulation and
experimental trials conducted on our campus and Hong Kong International Airport confirm that
Chameleon is able to adapt the radio map to signal environment, and achieves low localization
error despite signal changes.
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