【作者】 李俊峰；

【导师】 庞伟正；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2005， 硕士

【摘要】 本论文对无线通信网络中基于时间测量值的无线定位技术进行了研究。通过分析国内外相关研究现状,本文对现有多种定位方法进行了分析,基于科学的定位精度评价指标,在多种信道环境下对现有的基本定位算法进行了仿真。仿真结果表明:Taylor算法和Chan氏算法的定位精度高且易于实现。文中通过均方根误差对几种基本定位算法的性能进行了评价,并研究了多种参数对定位算法的影响,包括蜂窝小区的大小、参与定位的基站个数、测量误差、信道中的非视距传播误差。仿真结果表明:Taylor算法和Chan算法在不同环境和仿真条件下各有优缺点。然而,为了使定位精度能达到E-911的要求,还需要对基本定位算法进行修正和改进。 在上述研究的基础上,本论文提出了两种新的定位算法:基于到达时间差的遗传算法和粒子群算法。并在相同的仿真环境下,将遗传算法和粒子群算法与性能优良的Taylor算法和Chan算法进行了对比。仿真结果表明:这两种算法能显著地提高定位精度。更多还原

【Abstract】 This thesis aims at the research of wireless location technology based on time-related measurements in Wireless Communication System.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, the corresponding performance is evaluated by RMSE. 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 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, two new algorithms called Genetic Algorithm and Particle Swarm Optimization based on TDOA measurements is put forward. In the research, Genetic algorithm and Particle Swarm Optimization algorithm are put in the same environment for simulation and evaluation with Taylor and Chan Algorithms. The results show that, Genetic algorithm and Particle Swarm Optimization can improve significantly the location performance.更多还原