  Given that the accuracy of range-based positioning techniques generally
increases with the number of available anchor nodes, it is important to secure
more of these nodes. To this end, this paper studies an unsupervised learning
technique to obtain the coordinates of unknown nodes that coexist with anchor
nodes. As users use the location services in an area of interests, the proposed
method automatically discovers unknown nodes and estimates their coordinates.
In addition, this method learns an appropriate calibration curve to correct the
distortion of raw distance measurements. As such, the positioning accuracy can
be greatly improved using more anchor nodes and well-calibrated distance
measurements. The performance of the proposed method was verified using
commercial Wi-Fi devices in a practical indoor environment. The experiment
results show that the coordinates of unknown nodes and the calibration curve
are simultaneously determined without any ground truth data.
