RSSI辅助的蒙特卡罗盒定位算法

针对以蒙特卡罗为基础的几种无线传感器网络定位算法普遍存在定位精度和采样效率低的问题，文中提出了一种RSSI辅助的蒙特卡罗盒定位算法（RAMCB）。通过实验构造出符合实际环境的RSSI和距离区间的映射关系数据库；在定位阶段，未知节点利用来自一跳和两跳锚节点的RSSI值查询数据库，得到与一跳和两跳锚节点的距离区间，利用距离区间建立更为精确的采样箱，以提高采样效率；未知节点根据样本到一跳、两跳锚节点的估计距离和实际距离的差值来动态赋予样本的权值。仿真结果表明：RAMCB算法能有效提高定位精度和采样效率。

RSSI Assisted Monte Carlo Localization Boxed Algorithm

In view of the low localization accuracy and sampling efficiency problems that generally exist in the localization algorithm based on Monte Carlo in WSN. a RSSI Assisted Monte Carlo Localization Boxed （ RAMCB ） algorithm is presented. A database of the mapping between RSSI and distance scopes suited to realities is created by experiment. In the localization stage, an unknown node uses RSSI values from one-hop and two-hop anchors to query the database,then the distance scopes to one-hop and two-hop anchors are ob- tained, use the distance scopes to establish a more accurate sampling box to improve the sampling efficiency. An unknown node dynami- cally gives samples weights according to the difference between estimated distances and actual distances from samples to one-hop and two -hop anchors. The result of simulation demonstrates that RAMCB can effectively improve localization accuracy and efficiency.