改进指纹强度下的WiFi室内定位算法

目前的室内定位算法利用信号传播模型求出信号强度后直接进行求解定位,使得定位误差较大.为提高定位精度,提出利用信号能量的欧氏距离方法进行加权,然后对改进后的信号强度进行阈值滤波加均值滤波双重处理.定位阶段,在K最近邻算法基础上利用距离的倒数作为加权函数的算法进行定位.经仿真结果表明,改进后的算法相比于一些典型的定位算法,定位精度有较大提高.

WiFi indoor location algorithm based on improved fingerprint intensity

The current indoor location algorithm is directly solved the position by calculating the signal intensity used signal propagation model,that making the position error is too large.In order to improve the positioning accuracy,the Euclidean distance method of signal energy is proposed to be weighted,and then the improved signal strength is processed by threshold filtering and mean filtering.Positioning stage,using the reciprocal distance as a weighted function based on the k nearest neighbor algorithm for positioning.The simulation results show that the improved algorithm can improve the positioning accuracy greatly compared with some typical localization algorithms.