Research On Wlan Based Indoor Location Estimation Technology

With peoples’s growing demand for location information, location-based serviceshave attracted more and more attention and shown great energy in many applications, suchas emergency, asset positioning, personalized information delivery and other areas. Inrecent years, WLAN based locationg system has become a hot research topic because itcan take advantage of existing WLAN resources, can be implemented simply in softwareand doesn’t cost too much.In this paper, we make a deep and systematic research on positioning technologybased on WLAN and location fingerprinting. Aiming at positioning accuracy, energyconsumption of mobile equipment, we propose corresponding solutions. Throughalgorithms comparison and experiments analysis, we prove the effectiveness andfeasibility of the program.First, with the location fingerprints measured in practical WLAN environments, thethesis analyzes the statistical characteristics of received signal strength indicator in theview of indoor position. Then we analyse the reasons of positioning errors, the importanceand priciples of wireless access point selection and methods to reduce positioning errors. Itprovides an experimental and theoretical basis for the desigen of location algorithms andimplemention of positioning systems.Secondly, as mobile terminal equipments are limited in computing power, storagecapacity and energy, the thesis puts forward a certain kind of WLAN indoor positioningsystem based on energy efficiency. The system includes wireless virtual access pointspretreatment, clustering based on non-intermittent received signal strength indicator,selection of online wireless access points based on its spatial discrimination and rang,weighted nearest neighbors algorithm based on the spatial discrimination of receivedsignal strength indicator.Finally, we use the data obtained in real positioning environments into experiments,and evaluate the system’s performance from two aspects, positioning accuracy and energyefficiency. Experimental results show that the proposed energy efficiency indoorpositioning system improves positioning accuracy, while reducing the size of the database and the amount of data transfered between server and client.