中文摘要：

基于位置的服务（Location Based Service,LBS）逐渐成为蜂窝网提供给移动用户必不可少的服务之一,而如何能够快速、准确、高效地获取移动终端的位置信息变得日益迫切.本文通过考察一种曾用于无线传感器网络（Wireless Sensor Network,WSN）节点的定位算法——Monte Carlo Localization（MCL）算法,将其移植到蜂窝网中用于移动终端节点在二维平面内的定位.此外,为了解决MCL算法计算量大而导致的计算能耗高这一问题,又引入了捕食搜索策略对MCL算法进行改进.文中对蜂窝网移动终端定位环境进行了仿真实验,分别对算法的收敛性、定位精度、位置预测样本数、定位时间、移动终端的移动速度和基站数量进行了测评并与其它定位算法进行了对比.实验结果表明,改进的MCL算法不仅在定位精度上优于三种TDOA算法（Fang,Taylor,Friedlander）,而且在定位计算量上明显低于原始MCL算法.由此可得出在权衡定位精度和定位计算量的条件下改进的MCL算法优于其他三种TDOA算法（Fang,Taylor,Friedlander）及原始MCL算法的结论.

英文摘要：

Location based service has become one of the indispensible services cellular networks must provide to the mobile customers. The issue of quickly, accurately and efficiently obtaining the location information of the mobile terminal nodes has become increasingly urgent. In this paper, we consider a Monte Carlo Localization algorithm that used to be applied in locating the mobile sensor nodes in a wireless sensor network. Then we adapt this algorithm in the positioning of mobile terminal nodes in the two-dimensional plane in cellular networks. Furthermore, a predatory search strategy is also introduced to improve the efficiency of the calculation and decrease the energy consumption. We have evaluated the performance of the improved Monte Carlo Localization algorithm through simulation experiments in terms of the algorithm＇s convergence, positioning accuracy, samples number, localization time, speed of mobile terminal nodes and the base stations number. The simulation results show that the improved Monte Carlo Localization algorithm has a better performance than the original Monte Carlo Localization algorithm and other time difference of arrival positioning technologies in the case of balancing localization accuracy and calculation efficiency.