基于自适应射频指纹地图的WSN室内定位算法研究

Indoor Localization Algorithm Research Based on Adaptive Radio Fingerprinting Map and WSN

针对目前基于无线传感器网络进行室内定位时由于节点间收发信号的强时变特性而造成的定位精度不高、自适应性差的问题,提出了一种基于自适应射频指纹地图的WSN室内定位算法。该算法利用固定位置处信标节点间的信号强度来实时刻画环境的动态变化,从而构建出自适应环境变化的射频指纹地图;实时定位阶段,利用贝叶斯估计法计算目标初始位置,通过有限状态自动机滤除目标移动过程中出现的不可能跳变位置。实验结果表明,该方法在增加环境自适应性的同时大大提高了定位精度。

In order to improve the positioning accuracy and environmental adaptability which is caused by the fluctuation of the received signal strength for the WSN-based indoor positioning systems,this paper presents a new indoor location algorithm which is based on adaptive radio fingerprinting map and WSN. It utilizes signal strength between beacon nodes at the fixed location to describe the environmental dynamic changes in real time and develops the adaptive radio fingerprinting map. In real-time positioning stage,it uses the Bayesian estimation method to get target initial position,and then filter the impossible mobile target position by utilizing the finite state automation. Extensive experiments show that the proposed algorithm not only increases the environmental adaptability ,but also greatly improves the positioning accuracy.