Research On The RSSI Spatial Modeling And Receiving Equipment Deviation Of Indoor Positioning

With the development of information technology,the acquisition of location information is applied in many aspects of people's daily life,Location-based services(LBS)are developed from the outside to the interior.In recent years,WLAN technology has developed rapidly,while the user terminal equipment tends to be intelligent,wireless positioning has become the main way of indoor positioning,Indoor wireless signal transmission has a high complexity,the traditional rendezvous and positioning methods cannot be applied,the main content of this thesis is WIFI indoor positioning based on location fingerprint.This thesis analyzed the spatial distribution of RSSI(Received Signal Strength Indication),established a radio map based on RSSI spatial model.The reliability of radio map is analyzed by location fingerprint identification algorithm.The linear regression is used to modify the RSSI differences of heterogeneous devices,and the precision is analyzed and evaluated before and after the correction.In the RSSI space modeling phase.Firstly,the RSSI probability distribution and spatial separability in complex environment are verified by RSSI acquisition experiment in indoor environment.Then,this thesis analyzes noise of the RSSI feature extraction phase and the discrete fingerprint library establishment phase.For RSSI observation noise,singular value elimination and Gaussian filtering are used to improve the SNR and variance of RSSI signal,The RSSI position fingerprint library is filtered by the neighborhood mean algorithm to improve the matching degree of RSSI and space.Then,the cubic position interpolation algorithm is used to interpolate the discrete position fingerprint library,and the continuous RSSI space model radio map is established to improve the working efficiency of discrete fingerprint library.Finally,the positioning experiment is carried out by using deterministic and probabilistic fingerprint recognition algorithms respectively.The accuracy of the two methods is verified and the reliability and correctness of radio map are verified.In the positioning phase,the RSSI deviation between heterogeneous devices is analyzed and the size is explained by the dynamic and static RSSI acquisition experiment of heterogeneous equipment in indoor environment.This degree thesis analyzes the synchronization of dynamic RSSI sequences of heterogeneous devices,and shows that there is a positive correlation between the RSSIs of heterogeneous devices.Linear regression is used to model the linear relationship between RSSIs of heterogeneous devices and the model parameters are calibrated.The correctness and feasibility of the RSSI method for heterogeneous devices are explained by the positioning experiment before and after RSSI correction.