RSSI-based smooth localization for indoor environment

Radio frequency (RF) technique, for its better penetrability over traditional techniques such as infrared or ultrasound, is widely used for indoor localization and tracking. In this paper, three novel measurements, point decision accuracy, path matching error and wrong jumping ratio, are firstly defined to express the localization efficiency. Then, a novel RSSI-based smooth localization (RSL) algorithm is designed, implemented, and evaluated on the WiFi networks. The tree-based mechanism determines the current position and track of the entity by assigning the weights and accumulative weights for all collected RSSI information of reference points so as to make the localization smooth. The evaluation results indicate that the proposed algorithm brings better localization smoothness of reducing 10% path matching error and 30% wrong jumping ratio over the RADAR system.