Information fusion for indoor localization

This paper describes a fusion approach to the problem of indoor localization of a pedestrian user, in which PNS measurements, cartographic constraints and ranging or proximity beacon measurements are combined in a particle filter approximation of the Bayesian filter. Some critical issues are also addressed, such as taking the constraints into account, monitoring the degeneracy of the weights and the sample depletion in terms of the effective sample size, detecting track loss, and recovering from a detected loss.