Pedestrian navigation in harsh environments using wireless and inertial measurements

The popularity of positioning satellite systems in open areas has led to a high demand for systems suitable for harsh environments, where the former fail. Wireless localization and inertial navigation have emerged as the most valuable alternatives to offer positioning in such environments. However, the characteristics of the wireless propagation channel in harsh environments are dynamic and unpredictable while the errors in inertial navigation rapidly increase with time. In this paper, we present a general framework and algorithms for data fusion in navigation systems. The presented techniques combine both wireless and inertial measurements. To assess the proposed methods, we collected measurements from commercial wireless devices and low-cost inertial sensors in a real indoor environment. The experimental results show the remarkable performance of the proposed method, capable of reaching a sub-meter accuracy.