在非视距环境下数据融合的无线定位算法

从数据融合以及增加测量参数两个不同角度分别介绍了非视距环境下定位的方法.数据融合基于基站选择的方法,通过3层融合得到位置估计,而增加测量参数则是基于经典TDOA/AOA混合定位,在测量方程中加入校正因子,通过逐步迭代的方法逐步减小非视距影响,从而提高定位精度.仿真表明:非视距环境下,增加测量参数的定位精度要高于数据融合,并且方法比较简单.

The Data Fusion Wireless Location Arithmetic under the NlOS Environment

The paper introduces the wireless location in the real surroundings from the different angle of the data fusion and adding the measurement parameter,and the data fusion is based on the method of the choice of BS to get the estimation of the location by the way of three layers'data fusion;then the method of adding measuring parameter is based on the classic TDOA/AOA algorithm,adding the amend factor in the equator.The way of iteration gradually decreases the reflection of the NLOS to get more accuracy.The simulation shows that the accuracy of the adding the measurement parameter betters the data fusions,and the method is more simple.