1 research outputs found
Indoor Positioning using Similarity-based Sequence and Dead Reckoning without Training
For the traditional fingerprinting-based positioning approach, it is
essential to collect measurements at known locations as reference fingerprints
during a training phase, which can be time-consuming and labor-intensive. This
paper proposes a novel approach to track a user in an indoor environment by
integrating similarity-based sequence and dead reckoning. In particular, we
represent the fingerprinting map as location sequences based on distance
ranking of the APs (access points) whose positions are known. The fingerprint
used for online positioning is represented by a ranked sequence of APs based on
the measured Received Signal Strength (RSS), which is refereed to as RSS
sequence in this paper. Embedded into a particle filter, we achieve the
tracking of a mobile user by fusing the sequence-based similarity and dead
reckoning. Extensive experiments are conducted to evaluate the proposed
approach.Comment: 18th IEEE International Workshop on Signal Processing Advances in
Wireless Communications (SPAWC 2017