Researches On Localization Technology In Wireless Communication System

This paper mainly deals with wireless cellular localization algorithms, which are based on time measure values and angle measure values. First of all, several major methods for wireless cellular localization are introduced in this paper. The detailed localization formulae are presented for TDOA system, the multi-solution and non-solution problem of locating formulae are studied, the relations between the distribution of ambiguity and measure stations are found out, the methods to eliminate part of the ambiguity are also presented. Meanwhile, the reasons to produce non-solution are analyzed, and the next-to-best location method under non-solution conditions is discussed.Secondly, several channel models suitable for mobile localization and several kinds of localization errors express that have established the foundation for the localization simulation and the improvement of algorithm are introduced.Thirdly, on the basis of analyzing present localization technology and algorithm, this paper puts its emphases on TDOA and AOA. TDOA localization algorithm based on the BP neural network, AOA location algorithm based on the RBF neural network, TDOA/AOA localization algorithm based on the RBF neural network, TOA/AOA localization algorithm based on the RBF neural network are presented. 4 kinds of algorithms described above all utilize the neural network to correct to NLOS error first, then utilizes the corresponding localization algorithm to carry on the localization. The simulation results show its location accuracy is significantly improved and the performance of these algorithms is better than the algorithms not correcting NLOS error under different kinds of channel environment.Then, localization algorithm based on the BP neural network is presented. The measurement of AOA,TOA and TDOA provided by mobile base station is fused to locate mobile. The fast study and non-linear approach capacity of the neural network is made use of to apply in complicated multi-path environment. The simulation results indicate that the uncertainty of location and the effect of bad basement position are avoided while the cellular localization algorithm based on the BP neural network is used. Its location accuracy is significantly improved under complicated multi-path environment.Finally, TDOA/AOA data fusion location algorithm in LOS environment, TDOA/AOA data fusion location algorithm in NLOS environment and TDOA/AOA data fusion location algorithm based on the RBF neural network are proposed. The simulation results indicate that the location accuracy is significantly improved and the performance of this algorithm is better than using TDOA location algorithm and AOA location algorithm alone under different kinds of channel environment.