Research Of Indoor Location Technology Based On Zigbee Of Wireless Sensor Network

In recent years, Wireless Sensor Network is widely applied in military, civil and other fields for the WSN nodes are featured as low in power, cost-effectiveness and convenient to place. It’s very important to known how to obtain the sensor nodes’ position before the WSN be widely applied in such field. So the research on more efficient and fast localization algorithm of WSN is really a popular topic.First of all, the system architecture and mainly application fields for WSN are summarized based on the study of a lot of related literatures. In this thesis, the criterion of performance evaluation and algorithms, the taxonomy for wireless sensor networks localization systems are described, the principles and characteristics of recent representative localization approaches are discussed and presented.Secondly, we focused on the range-based localization algorithm based on the received signal strength indicator (RSSI) for its low power and high precision, and then analyses several node localization algorithms based on RSSI ranging model in detail. We applied C51RFWSN platform to establishing a precise distance measurement model, Gaussian filter is used to reduce impact of the accidental error of measured RSSI value in specific distance, and using linear regression analysis to optimize the value of A,n in the ranging model. Through theory and actual measurement it shows that signal attenuation parties up irregularities, that we had to add a parameter of degree of irregularity(DOI) in order to establish a more precise indoor ranging model.Finally, we simulated and analyzed trilateration positioning method, maximum likelihood estimation method and min-max location method through MATLAB to model the wireless sensor network environment based on the ranging model. And by altering the ratio of anchor node, the total number of nodes and the value of DOI, the scalability and adaptability of these algorithm are analyzed. Simulation results shows that Min-Max positioning algorithm has larger position error on the edge of cross border and found that was caused by the unique principle. We propose the cross border detection method to resolve the problem that the blind nodes around the edge of localization region have larger position error. The simulation result shows that the improved method can effectively improve the position accuracy of blind nodes around the localization edge.