| With the rapid development of 5G mobile communication technology and the large-scale commercial use of 5G networks,there are new ways to realize indoor positioning.Nowadays,people's demand for indoor positioning is no less than outdoor positioning.Millimeter wave and large-scale antenna arrays,as the most important technologies adopted by 5G,have huge potential advantages in indoor accurate positioning.On the one hand,the millimeter wave has good directivity and can obtain high-precision ranging and direction finding information;on the other hand,the large-scale antenna array has a higher-resolution beam,which can further obtain higher-precision ranging and angle measurement information.These advantages can provide more accurate TOA/AOA/AOD estimates for positioning technology based on Time of Arrival(TOA),Angle of Arrival(AOA)and Angle of Departure(AOD),thereby provide a new technical approach for the realization of indoor high-precision positioning.To this end,this thesis mainly studies the delay and angle information estimation technology and positioning algorithm based on 5G millimeter wave and MIMO antenna arrays in indoor environments.The main work of this thesis is divided into the following parts:1.Realize the joint estimation of positioning parameters TOA/AOA/AOD in the millimeter wave channel.Considering the sparseness of the millimeter wave MIMO channel,this thesis uses the DCS-SOMP channel estimation algorithm based on distributed compressed sensing to reconstruct the sparse channel and estimate the AOA/AOD angle parameters.The estimated channel and angle parameters are used to further solve the problem to obtain the TOA delay parameter.2.The traditional DCS-SOMP-based channel estimation algorithm has insufficient performance.The iteration termination condition in the algorithm is only related to the signal sparsity.When the sparsity set in the algorithm is less than the actual channel sparsity,its performance will be significantly reduced.Accordingly,an improved channel parameter estimation algorithm based on DCS-SOMP is proposed.In the improved algorithm,the iteration termination condition is modified,and the sparsity of the signal is no longer used as a known condition.The simulation results show that the performance of the improved algorithm is better than that of the traditional algorithm.It can effectively eliminate the influence of signal sparsity on the algorithm performance while maintaining better parameter estimation accuracy.3.In view of the weak ability of millimeter wave to penetrate walls and it is impossible to use more than three base stations for positioning in most indoor scenarios,this article focuses on how to use a single base station to achieve indoor mobile station positioning,which is divided into LOS and NLOS environments for analysis.discuss.First,in the LOS environment,study how to use the positioning algorithm based on TOA/AOD joint estimation to realize mobile station positioning,and in the NLOS environment,study the use of two positioning algorithms based on TOA/AOA/AOD joint estimation,respectively based on LPMD line positioning Algorithms and positioning algorithms based on particle swarm optimization to achieve the positioning of indoor mobile stations.The simulation results show that the above three positioning algorithms have good positioning accuracy.4.A single base station positioning algorithm based on reflection path and virtual base station is proposed for indoor NLOS environment.The algorithm generates a virtual base station based on the known reflection surface,then matches the reflection path with the virtual base station,and finally uses the virtual base station to locate the mobile station.The simulation results show that the algorithm proposed in this thesis has achieved better positioning accuracy. |
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