RSSI- based localization and tracking algorithm for indoor environments

The paper reports the preliminary results of a RSSI-based localization algorithm that implements an exhaustive exploration of the data space, i. e. the power maps of the received signal in an indoor environment. The technique takes advantage of previous experimental results that served to calibrate the signal level simulated by a ray tracer. Numerical precalculated maps include perturbed scenarios that simulate actual conditions in which the signal fluctuates. The localization algorithm draws at random a perturbed map and it extracts the power values corresponding to the probe location. Then, an exhaustive exploration of the spatial domain over an average map is performed to single out the minimum of a cost function expressing the residual between the power values of the test point and those of the candidate points.