Research On Indoor Estimation For Probability Matching Based On Historical Path

With the rapid development of pervasive computing technology, people are increasingly expecting more convenient services provided by the ideal ubiquitous computing environment. Among them, an accurate estimate of user location is an important prerequisite and basis for universal services under ubiquitous computing environment. Although location technology in GPS (global positioning system) is already mature, it usually just suits in outdoor open space. At the same time, telecommunications network based location technology cannot meet indoor positioning requirements due to ideal positioning accuracy unachieved.With the widespread application of wireless local area network (WLAN) on IEEE 802.11 protocols in reality, WLAN-based indoor positioning turns to be feasible. In addition, among these location technologies, it has a good many advantages such as full use of the existing wireless network infrastructures, without additional hardware, great superiority in cost of building position system and so on.Aiming at those problems that the traditional Probability Matching Model is lack of position matching accuracy, and the traditional location algorithm cannot estimate position precisely when only one or less signal source indoor, this paper proposes a ProHI algorithm for location which bases on probability matching combined with the shortest history path. Besides, a WLAN-based indoor positioning system has been completed. Experiments show that the proposed positioning method is practical and can meet the demand for indoor positioning.Specifically, in aspect of signal matching and path matching, this paper does research work as follows.Firstly, for location by signal matching, a more accurate signal model was built with Gaussian process after analyzing the influence of environmental to wireless signal. Then the traditional model was improved by combining the logarithm of traditional probability matching computation with simple propagation model, which increases the accuracy of location.Secondly, in the case of single signal source indoor, the location algorithm of the shortest historical path matching based on probability matching positioning model was approached. This algorithm obtains RSS (Received Signal Strength) after several effective signal collections at short intervals or at a short moving distance. After that, the RSS is mapped to locations according to which the shortest historical path is then calculated. At last, the end point of the final shortest path is taken as estimated location.Finally, based on the research work, a WLAN-based positioning system prototype is designed, and future prospect is put forward.