RFID Based Indoor Moving Target Location Algorithm And System Design

With the rapid development of wireless technology,indoor positioning technology has attracted increased attention.In the indoor environment such as offices,hospitals,shops,factories and other environments,GPS and other equipment is difficult to have ideal positioning accuracy.Infrared,WIFI,Bluetooth and other traditional positioning technology,because of their complex system setup,expensive equipment,non-satisfactory positioning accuracy and other shortcomings,they are difficult to be widely applied in practice.The radio frequency identification technology has become one of the most promising application technologies in this century because of its low cost,non-contact,non-line of sight,and stable operation in harsh environment.However,the noise of indoor environment,multi-path effect,and the environment noise are inevitable,how to obtain higher localization accuracy in such environment,and design an efficient and stable positioning algorithm with acceptable precision is particularly important.This thesis briefly introduces the main ideas of several classical algorithms,and points out some defects in these algorithms.Among the various localization algorithms,the LANDMARC system theory and Kalman filtering algorithm have received the most attention.To rely on sensor positioning results,its stability and accuracy is usually not satisfactory,this thesis adopts the improved BVIRE algorithm using the adaptive Kalman filtering algorithm,and the RFID localization technique is used in the indoor environment.The traditional BVIRE algorithm can easily lead to unstable results due to several non-ideal environment factors.In this thesis,the adaptive Kalman filter is developed to overcome this disadvantage.Secondly,the BVIRE algorithm in indoor environment is not strong enough to adapt to the environment,and the positioning result fluctuates violently.The data processing also help get the satisfactory positioning results.Finally,the indoor positioning experiment platform is established and the proposed algorithm is verified in the experimental platform.The simulation and experimental results show that the proposed algorithm improves the indoor positioning accuracy and improves the robustness of the positioning system significantly.At the same time,through the layout of the experimental environment,tag placement,antenna and reader and other parameters configuration,we obtain a satisfactory indoor positioning accuracy...