Implementation Of TDOA Location Technology Based On Cultural Swarm Intelligence

Cellular wireless location technology is a novel mobile technology and has a betterapplication future. By using of existing cellular mobile communications network, locationmethods use characteristic parameters relative to position of time-of-arrival (TOA),time-difference-of-arrival (TDOA) and direction-of-arrival (DOA) to complete mobile userlocation. This thesis aims at the research of wireless location technology based ontime-related measurements in wireless communication system.The thesis analyzes the domestic and foreign related research of present situation, andgives several essential methods of mobile location. After that, the mathematical model ofTDOA is established, and Chan algorithm, genetic algorithm (GA) and particle swarmoptimization (PSO) algorithm based on TDOA location model are presented and analyzed.Computer simulation is used to provide simulation results of above algorithms. Simulationresults show that all the algorithms have the advantages and disadvantages. The Chanalgorithm has poor location accuracy and very quick operating speed. On the contrary, theGAand PSO have a high accuracy and a long convergence time.Based on the above investigation, five location algorithms which are called as CPSOalgorithm, CSFLA, SFLA, Chan-CPSO algorithm and Chan-CSFL algorithm based onTDOA measurements are put forward. Carrying on the computer simulation to them underthe same environment, the simulation results show that if the population size is big enough,the proposed algorithms are robust and can find the coordinates. They have a higher accuracythan Chan algorithm and a faster convergence time than genetic algorithm.At last，we useGraphical User Interfaces（GUI）to implete mobile location based on intelligence computing.