Research On LTE Positioning Technology Based On TDOA Parameter Estimation

In recent years, with the rapid development of the mobile communication industry as well as the internet technology and the intelligent terminal service, wireless mobile positioning technology is drawn more and more attention by domestic and foreign scholars, especially LTE positioning technology. However, the NLOS propagation of signals of LTE location system is still a big problem, which will have a great effect on the positioning accuracy. In this context, the positioning parameter estimation and wireless positioning algorithms as well as NLOS error elimination of LTE positioning technology are researched in this thesis by combining the wireless location technology and the LTE technology. The main work of this thesis is as follows:In the aspect of time-delay parameter estimation, GCC algorithm is studied in this thesis, and a LTE time-delay estimation optimization method based on Genetic Algorithm in NLOS environment is studied. The method which uses the arriving angle of signal as the cofactor of the fitness function is used to reduce the influence of NLOS error. The performance of the researched optimization algorithm and the classical GCC algorithm is compared.In the part of positioning algorithm, the common wireless positioning algorithms are studied in this thesis and the comparison of the simulation performance among various algorithms is done in three aspects, including the measurement error, the number of base stations and the radius of base stations. In the end, CHAN algorithm in LOS and NLOS environment is studied. Also based on the study of CHAN algorithm in LOS environment and the analysis of statistical characteristics of NLOS error, a method which improves the CHAN performance in the case of NLOS by optimizing the NLOS TDOA measurement error is researched.The simulation result shows that the performance of the proposed time-delay optimization algorithm based on Genetic Algorithm in NLOS environment is better than the GCC algorithm. Also, the improved CHAN algorithm of this thesis can achieve better positing performance in the environment of NLOS.