Research On Single/Double Base Station Localization Technology In Nlos Environment Based On Optimization Theory

With the continuous development of information technology,there is an increasing need for accurate positioning in all walks of life.Although today’s base station construction has met the requirement that most areas can be covered by three or more base station signals,there are still a small part of remote areas or indoor environment can only be covered by one or two base stations.Therefore,it is of great significance to study the NLOS positioning algorithm of single / double base station for accurate positioning of the entire region.Therefore,the main work of thesis is as followsFirstly,by consulting a large number of existing related documents,the research status of single/double base station scenarios location algorithms based on optimization theory at home and abroad is reviewed and the shortcomings of the existing localization algorithms is summarized.Secondly,five commonly used positioning methods are introduced,including Time of Arrival(TOA),Angle of Arrival(AOA),Time Difference of Arrival(TDOA),Received Signal Strength(RSS)and hybrid positioning,three indexes used to evaluate the positioning accuracy,and two commonly used scatterer models.Three methods of positioning based on optimization theory are analyzed,and the positioning performance is simulated and compared.Thirdly,in the double base station scenario,several algorithms based on the optimization theory are analyzed,including the traditional localization algorithm without considering the scatterer information,the localization algorithm based on the scatterer information and the localization algorithm using the scatterer as the virtual base station.The performance gap between the grid method and the interior point method is explored,and an improved positioning algorithm based on the ring model is proposed,which combines the grid method and the selective average method.The simulation results show that under the ring model,the positioning error of the improved algorithm is significantly reduced compared with other algorithms.Then,in the single base station scene,the TOA/AOA reconstruction method and the localization method based on the Angle of Departure(AOD)information are analyzed and studied,and the constraint conditions of the localization algorithm based on AOD information are improved.The improved algorithm adds another constraint to the Mobile Station(MS)feasible region,that is,the point whose distance is the corresponding TOA value of the base station,the point whose angle is AOA value is set as a point,the point whose distance is the corresponding TOA value of the base station,the point whose angle is AOD value is set as B point,and the MS should be located on the line ab.Through this geometric constraint,the optimal search area of the original NOA algorithm is further reduced.The simulation results show that the location performance of the improved algorithm is better than that of the original NOA algorithm.Finally,the research work of thesis is summarized,and the follow-up research content and possible improvement direction are proposed.