Research On Multi Source Information Combined Location Of Mobile Terminal Based On Wireless Node

With the development of mobile internet and the popularization of smart terminals such as phones,panel computer,PADs,notebooks,wearable devices,and the rapid growth of the performance of Internet of things equipment,the public demand for LBS is increasing day by day,and the key to achieving LBS is the precise location information.However,in urban canyons,one of the most widely used scenarios,due to the tall buildings and short spacing of tall buildings,the signals received by GNSS receivers are affected by building blockages,reflections,diffractions and visible satellite stripe distributions,resulting in positioning errors is large or even impossible to locate.In these scenarios,wireless nodes such as Wi-Fi,Bluetooth and communication base stations are intensively signalized,so the mobile terminal can use wireless node signals to achieve navigation positioning in this area.In this thesis,the mobile terminal uses the wireless node location as background,analyzes the problem of the lack of positioning accuracy of the wireless node,and analyzes the filtering performance and existing problems of KF,EKF,UKF and PF algorithms in detail.For the problem of particle degradation in the particle filter process,the particle swarm algorithm is studied,and an improved bird swarm algorithm is proposed based on this.The improved bird swarm algorithm is based on bird foraging,vigilance,and flight behavior for given problems.Provides the development and exploration of the best solution.This algorithm can be used as a recommended distribution of PF to improve the degradation of particles during PF operation.Through experimentation,the average error is reduced by 18% compared with the traditional method when using particle filter algorithm,and the average error is reduced by 26% compared with the traditional method based on the bird filter algorithm.At present,map matching technology is mostly used to correct the GNSS real-time positioning data.With the development of urban transportation,road network data become more and more detailed,the development of communication technology in recent years,the construction of hidden Markov models in the process of positioning using communication base stations in urban canyon environment,the use of Viterbi algorithm to improve the positioning point and the map matching rate,thus achieve an improved map matching algorithm.Through experiments,the results show that the single-point error of positioning data after map matching is significantly reduced.