Mobile Sensor Network Localization in Harsh Environments

The node localization problem in mobile sensor networks has recently received significant attention. Particle filters, adapted from robotics, have produced good localization accuracies in conventional settings, but suffer significantly when used in challenging indoor and mobile environments characterized by a high degree of radio irregularity. We propose FuzLoc, a fuzzy logic-based approach for mobile node localization in challenging environments and formulate the localization problem as a fuzzy multilateration problem, with a fuzzy grid-prediction scheme for sparse networks. We demonstrate the performance and feasibility of our localization scheme through extensive simulations and a proofof-concept implementation on hardware, respectively. Simulation results augmented by data gathered from our 42 node indoor testbed demonstrate improvements in the localization accuracy from 20%-40% when the radio irregularity is high.