Research On Tsoa/aoa Positioning Technology In Cdma Network

In this thesis, a novel TSOA/AOA positioning system based on a third party location apparatus is proposed. This system uses the TSOA (Time Sum of Arrival) measurements and AOA (Angle of Arrival) measurements to locate a Mobile Station (MS) in CDMA cellular network, which is of great significance for ensuring the national security, fighting against criminals, and providing emergency relief services.First, the principle of the TSOA/AOA positioning system is presented associated with analysis of CDMA2000 physical layer protocols, and the scheme of obtaining the position parameters is introduced.Second, the CRLB(Cramer-Rao Lower Bound) and GDOP(Geometric Dilution of Precision) of the TSOA/AOA positioning system in Gaussian noise environment are derived and thoroughly analyzed. The minimum value of the GDOP when position using single apparatu is discussed and a series of conclusion essential for the layout of positioning apparatus are obtained.Third, Chan and Friedlander positioning algorithm are extended from TDOA into TSOA positioning system, and two novel TSOA/AOA positioning algorithm are proposed:―A Non-iterative TSOA/AOA Positioning Algorithm with Explicit Solution‖and―A TSOA/AOA Algorithm Based on Least Square and Taylor Series Expansion‖. Simulation results indicate these two methods perform better than Chan and Friedlander algorithm and their accuracy could attain the CRLB when the noise is Gaussian.Fourth, multi-path delay channel models for TSOA/AOA positioning both in micro-cell and macro-cell environment are designed based on Geometrical-Based Single Bounce Statistical Channel Model(GBSBM) model, and the statistics of the TSOA and AOA error in NLOS(Non Line of Sight) environment are attained. Then, an AOA measurements restructuring algorithm using Kalman filtering and a TSOA measurements restructuring algorithm using modified biased Kalman filtering are proposed. The simulation results show that the change of NLOS/LOS status can be identified accordingly and the NLOS errors can be mitigated effectively.Finally, a mobility target tracking system based on particle filtering is proposed. The dynamics of the system under consideration are described by a nonlinear state-space model. The technique allows for accurate estimation of both MS's position and speed. Simulation results indicate this method can achieve higher accuracy than extended Kalman filter tracking algorithm.