Research Of RSSI-based Indoor Location Algorithm In Wireless Sensor Network

Wireless sensor network technology is a modern product,which combines sensing technology,micro-processing technology and wireless communication technology.With the rapid development of wireless sensor network technology and the joint application of wireless sensor networks and the Internet,wireless sensor network has drowned great attention.Wireless sensors have the advantages of low cost,easy deployment,strong scalability and selforganization,which have made them get great progress in military,medical,smart home and other fields.As a key technology of wireless sensor networks,location technology provides wireless sensor networks effective means for route optimization,network management optimization and coverage assessment.Therefore,the node location algorithm has also become an important research direction.Based on the existing theory of studying indoor positioning and positioning algorithms,this article deeply studies the centroid location algorithm based on RSSI,analyzes the influence of RSSI value,proposes an improved algorithm and further study the feasibility of applying its ranging method to a three-dimensional positioning model.The main work of this paper is as follows:(1)The wireless sensor network positioning technology and classification are introduced in detail,focusing on the principle of measuring distance location based on TOA,TDOA,AOA and RSSI.A comparative analysis of these technical limitations will illustrate the performance evaluation indicators of several common positioning systems.(2)Explaining the two-line model,regular model and irregular model of radio signal propagation in the environment,we focus on the latter two ranging models.The factors that affect RSSI value in the model of Logarithmic dispersion are explored: path loss A and path attenuation coefficient n.With MATLAB as the simulation platform,the simulation analysis of each model is carried out to study the spatial transmission characteristics of the wireless signal.the optimization of the model is given to make it more similar as the actual environment.(3)Based on RSSI gaussian correction centroid localization algorithm is given in paper.We also put forward a gaussian filtering for RSSI value with the filtering threshold judgment.Then we screen the RSSI values,perform ranging processing on it and perform centroid positioning to estimate the unknown node position.The simulation of the improved algorithm is performed through the MATLAB platform,and the positioning error is compared from the number of beacon nodes and the communication distance.The simulation experimental results show that the centroid algorithm based on RSSI gaussian correction decreased by 27.3% under different numbers of nodes and decreased by 28.3% under changing communication radius.Compared with traditional algorithms,the improved algorithm has better positioning accuracy.(4)The two-dimensional plane positioning is extended to three-dimensions,and the influence of line-of-sight and non-line-of-sight environments on the positioning model is determined and the RSSI-based ranging data fitting processing will be performed.Predictive data location information and actual location information are compared and analyzed.The mean root-mean-square errors of the two sets of random data are calculated as: 1.3422 and 1.1351 respectively,which verifies the feasibility of calculating the three-dimensional space positioning model of terminal coordinates in the context of non-line-of-sight propagation.