This study proposes a method based on access point (AP) selection and adaptive
pattern-matching for Wi-Fi indoor positioning (ASAPM). In the proposed ASAPM, a box plot
algorithm is used to remove received signal strength (RSS) outliers in samples received from APs in
order to smooth the RSS. Subsequently, we analyzed the RSS variations for selecting the top-N APs
with the least interference. Moreover, we analyzed the history of the positioning results to estimate the
direction and distance of users in subsequent positions in order to reduce the pattern-matching time
and computational overhead of the positioning system. The simulation results revealed that the
average positioning error, average maximum positioning error, and average pattern-matching times of
ASAPM were 36%, 51%, and 57% lower than the three compared strategies, respectively. These
findings show that ASAPM could reduce the computational overhead; moreover, it is suitable as an
indoor-positioning service for mobile devices.
關聯:
Journal of Applied Science and Engineering 19(3), pp.337-346