Research Of Indoor Wireless Positioning System Algorithm

With the development of science and technology, especially the rapid development of mobile Internet, indoor navigation and positioning has become a hot topic, and location based service become a sunrise industry. GPS application in outdoor has a good effect, however, GPS signal in the indoor environment is weak or not at all, so the positioning effect is poor even unable to locate. Therefore the positioning of indoor environment becomes an important research direction in the field of positioning. The wireless sensor network technology is a new type of indoor positioning technology solutions, it has attracted many experts and scholars studying.In this thesis, the ZigBee wireless sensor network and UWB wireless sensor work are studied. Under the premise of introducing the research background and meaning, this thesis analyzes the several common kinds of wireless location technology in detail, and comparing the wireless location technology, analyzing the advantages of ZigBee technology and UWB technology, but the complex indoor environment restricted the ZigBee indoor positioning' precision, the goal of this thesis is without any other hardware equipment, and put forward new locating method to study. This thesis also studies the UWB positioning method.After two years study, this thesis proposes six ZigBee reference nodes to locate, and using Kalman filter and Gauss filter processing the raw data. Through the experiment, in locating method of fingerprint database to establish fingerprint database and online positioning phase using Kalman filter and Gauss filter to process the original data, then adopt the most adjacent localization algorithm, weight adjacent localization algorithm and the Bayesian algorithm, finally finding using Kalman filter and Gaussian filter, the system's average positioning accuracy have improved. And this thesis proposes weighted adjacent localization algorithm based on the fuzzy clustering and use it on the ZigBee positioning system, in the best case, the system of position precision is 1.47 m. This thesis puts forward the path loss model based on particle swarm optimization algorithm, and use it on the ZigBee positioning system. In the best case, the system average position precision is 3.13 m. In addition, this thesis studies the UWB positioning system, and use the UWB positioning system collecting data and processing data for positioning, through analysis that the average precision is 0.245 m.