Research On Indoor Location Algorithm Based On Multidimendional Scale And RSSI

With the rapid development of information technology,today's society is becoming more and more informative.The information in the information society is also more and more important.The collection of information also occupies a greater proportion in people's lives.With the rapid increase of multimedia services and data services,people's demand for indoor positioning is also increasing.In indoor environments such as airport supermarket libraries,it often happens that the position of a certain person needs to be determined.However,in the actual positioning process,it is always susceptible to shadow attenuation,multipath effects and other factors that make the final result biased,so when positioning,select a relatively good positioning algorithm,you can effectively reduce the outside world The impact of the environment on the positioning process,so as to achieve accurate positioning of the target using relatively few network resources,obtain relatively high positioning accuracy,and complete the positioning of the target as efficiently as possible,so how to determine a relatively effective positioning algorithm is The practical application is particularly important,and the constant accuracy of positioning and the optimization of positioning algorithms are also more and more important challenges and useful research topics in the future.In this thesis,the principle of multidimensional scaling(MDS)location algorithm based on distance measurement is studied in detail,and the existing multidimensional scaling algorithm is based on the unified solution framework.When the position is located,more complex operations are required.After matrix-based decomposition and traditional multi-dimensional scaling algorithms are compared,the matrix decomposition algorithm can simplify the computation and can improve the tedious operation of positioning the moving points.Due to the indoor environment,RSSI is susceptible to shadow attenuation,multipath effects and other factors,resulting in biased results.Therefore,after detailed research on traditional RSSI positioning algorithms,this paper proposes an RSSI positioning algorithm based on the correlation coefficient of virtual anchor nodes.Improves RSSI positioning algorithm positioning accuracy.Finally,the thesis improves the correlation coefficient RSSI location algorithm and the multidimensional scaling algorithm based on matrix decomposition,uses the signals between the nodes to establish the dissimilarity matrix,uses the multidimensional scaling method to solve the relative coordinates between the nodes,according to the model transformation,and finally The particle swarm algorithm was used to optimize the parameters,so as to obtain the coordinates of the moving point,and verified by simulation experiments.Finally,the positioning of the target node can be satisfied.