The Investigation Of Wireless Location Algorithms Based On Time-related Measurements

This thesis aims at the research of wireless location algorithms based on time-related measurements in Wireless Cellular Network.After analyzing the previous research in wireless location extensively,the thesis analyzes and compares,by simulation under some common mobile channel environments,the existing basic location algorithms. The simulation results show that,Taylor algorithm and CHAN algorithm are easy to realize and can achieve good location accuracy. Therefore,in order to evaluate the performance of the two basic algorithms in detail,two typical mobile communication channel models (COST 259 and T1P1) are employed for further detailed simulation,and the corresponding performance is evaluated by RMSE and CDF. In this simulation,many relative parameters are examined,such as the cell size,the number of base stations taking part in the location service,equipment measurement errors,NLOS effect,and the positions of BSs etc. The simulation results show that,Taylor algorithm and CHAN algorithm fit in various simulation environments. However,in order to meet the so-called E-911 demand,these algorithms must be modified.Based on the above investigation,a new hybrid location algorithm called TOA AOA Hybrid Location Algorithm is put forward. In the research,TOA AOA algorithm and TDOA AOA algorithm are put in the same environment for simulation and evaluation. The results show that,this hybrid location algorithm with angle measurements can make full use of the information provided by cellular network. Especially,when the AOA measurements obtained have relatively high accuracy,the location performance can be improved significantly.Based on the related research work,a new data fusion method is presented in this thesis. This method combines many technologies such as TOA,TDOA,AOA,hybrid algorithm and Bayesian Theorem etc.,and statistic characteristics is used to process the simulation results in order to achieve higher location performance.