基于菲涅尔理论的非训练式指纹定位法

Fingerprint matching localization with non offline training based on fresnel theory

针对免携带设备定位(device free localization,DFL)中,无线层析成像法(radio tomographic imaging,RTI)在线重构速度慢,指纹法(fingerprint matching,FM)离线训练量大,复杂度高等问题,提出了一种基于菲涅尔理论的非训练式指纹法。所提出的定位算法改变了传统指纹法需要实际测量的离线训练模式,采用非训练模式建立参考指纹库,降低时间复杂度,并模拟实际测量环境对参考指纹库进行误差修正,减弱环境的干扰,最后用加权K最近邻域法实现对目标位置的估计。在保证定位匹配速度的同时,满足定位精度的要求。

Device-free localization（DFL）is to estimate the location of object without carrying any electronic device.In allusion to problems such as low reconstruction speed of traditional radio tomographic imaging（RTI）,massive store capacity and time complexity of offline training in traditional fingerprint matching（FM）etc.,this paper proposed a localization estimation method with non offline training based on the theory of Fresnel.Firstly change of received signal strength（RSS）of links under the Fresnel region will be calculated,then change of RSS will be modified for satisfying some reality constraints,reference fingerprint database will be established.By establishing fingerprint database,capacity of training fingerprint database can be reduced effectively.Error of actual environment will be taken into consideration and correction will be made to weaken the environmental disturbances.Finally K-nearest neighborhood algorithm will be applied to the target positioning estimation.The simulation results show that this method not only can ensure the positioning speed while matching,but also can ensure positioning accuracy.