Research On Mobile Station Localization Technology Based On Single Scatterer Identification In NLOS Environment

With the rapid development of the information industry,people have higher and higher requirements for location-based services,and location technology has been widely used in various fields.How to obtain accurate target location information has always been the focus of wireless positioning technology research.In the line-of-sight environment,the existing algorithms have been able to achieve high-precision target positioning.However,in the nonline-of-sight environment,there are many factors that affect positioning accuracy,among which the non-line-of-sight error is the main source of target positioning deviation.At present,the problem of how to overcome the adverse effect of NLOS propagation error on positioning accuracy has not been thoroughly solved.For this reason,a new technology research on highprecision positioning of mobile station based on single scatterer identification is studied in this thesis.The main work of this thesis is as follows:Firstly,the domestic and foreign research status of mobile station localization technology based on scatterer information in non-line-of-sight propagation environment is summarized by reading literature,and the feasible research direction is pointed out.Secondly,the classical line-of-sight positioning algorithm is described,the positioning accuracy evaluation index is given,the influence of NLOS environment on the positioning accuracy is analyzed,and ROS and DOS channel models are mainly studied.Simulation results show that the positioning performance of the line-of-sight localization algorithm will be seriously degraded in NLOS environment.Thirdly,aiming at the problem of identification and matching problem of single scattering path from the same scatterer in NLOS environment,an identification and matching algorithm based on AOA/TOA double search is proposed in this thesis.According to the geometric position relationship between base station,single scatterer and mobile station,the algorithm firstly uses AOA measurements to locate the possible scatterers,and then judges whether the differences between TOA measurements and the distances from the base stations to scatterer are consistent,and the first identification and matching of single scattering path is completed.On this basis,the second identification and matching is performed.Simulation results show that the proposed algorithm has higher recognition rate and better performance.For the scene where AOD measurements can be obtained,the single scattering path identification and matching algorithm based on LPMD is studied and analyzed,and the theoretical derivation and proof of the algorithm are improved.Then,a MS localization algorithm based on virtual base station is proposed in this thesis.After completing the identification and matching of single scattering paths from the same scatterer,the TDOA/AOA hybrid positioning algorithm is used to first estimate the single scatterer position using the NLOS path information from the same scatterer,and then the scatterer is regarded as a virtual base station.The virtual base station with small position error and small distance error are used to locate the MS position,which realizes the transformation from NLOS localization problem to LOS localization problem.Next,in order to better evaluate the performance of the MS positioning algorithm proposed in this thesis,the positioning error CRLB of MS positioning method based on virtual base station is deduced.Firstly,the CRLB of the scatterer positioning error is derived,and the effect of the position error of the virtual base station on the distance error between the virtual base station and MS and MS positioning error is analyzed.Finally,the CRLB of MS positioning error is deduced.Simulation results show that the CRLB derived in this thesis is close to the CRLB of the LOS location algorithm,and the positioning error of the proposed algorithm is close to its CRLB in the simulation experiment.In addition,compared with other existing algorithms,the proposed algorithm has higher positioning accuracy and better performance.Finally,the contents of the research of this thesis is summarized and the direction of further research in the future is given.