摘要：Location-based service is one of the most popular buzzwords in the field of
U-cities. Positioning a user is an essential ingredient of a location-based
system in a U-city. For outdoor positioning, GPS based practical solutions have
been introduced. However, the measurement error of GPS is too big for it to be
used for U-campus services, because the size of a campus is smaller than that of
a city. We propose the Relative-Interpolation Method to improve the accuracy of
outdoor positioning. However, indoor positioning is also necessary for a
U-campus because the GPS signal is not available inside buildings. For indoor
positioning, various systems including Cricket, Active Badge, and so on have
been introduced. These methods require special equipment dedicated to
positioning. Our method does not require such equipment because it determines
the users position based on the received signal strength indicators (RSSIs)
from access points (AP) which are already installed for WLAN. The algorithm we
use for indoor positioning is a kind of fingerprinting method. However, our
algorithm builds a decision tree instead of a look-up table in the
off-line phase. Therefore, the proposed method is faster than the
existing indoor positioning methods in the real-time phase. We integrated
our indoor and outdoor positioning methods and implemented a prototype
indoor-outdoor positioning system on a laptop. The experimental results are
discussed in this paper. In implementing the prototype, we also implemented a C#
library function which can be used to read the RSSIs from the APs.
