A bio-inspired approach to WiFi-based indoor localization

In this paper, the problem of indoor localization is investigated using a bio-inspired approach. The proposed approach relies on the use of WiFi networks, which nowadays can be considered a commodity available in all indoor environments. WiFi signals are used to obtain estimates of the distance between a smart device, whose position needs to be estimated, and the fixed access points of the network, which are assumed to be in known positions. Once a given number of range estimates from each available access point has been acquired, proper range averages are performed to feed the proposed localization algorithm. According to the proposed approach, localization is formulated in terms of an optimization problem, which is solved using an algorithm inspired from particle swarm optimization. Such an algorithm has been integrated in an add-on module of JADE, which is intended to execute on the smart device whose position needs to be estimated, and which was tested in relevant indoor scenarios. Experimental results in tested scenarios are shown in the last part of the paper in order to evaluate the performance of the proposed bio-inspired localization algorithm.