Adaptive radio maps for pattern-matching localization via inter-beacon co-calibration

A growing number of location-based applications are based on indoor positioning, and much of the research effort in this field has focused on the pattern-matching approach. This approach relies on comparing a pre-trained database (or radio map) with the received signal strength (RSS) of a mobile device. However, such methods are highly sensitive to environmental dynamics. A number of solutions based on added anchor points have been proposed to overcome this problem. This paper proposes an approach using existing beacons to measure the RSS from other beacons as a reference, which we call inter-beacon measurement, for the calibration of radio maps on the fly. This approach is feasible because most current beacons (such as Wi-Fi and ZigBee stations) have both transmitting and receiving capabilities. This approach would relieve the need for additional anchor points that deal with environmental dynamics. Simulation and experimental results are presented to verify our claims.