一种基于TDOA二次加权的QWLS定位算法

A QWLS Positioning Algorithm Based on TDOA Quadratic Weighting

目前基于TDOA的定位算法——最小二乘法(Least Square,LS)不管在室内还是室外在定位精度要求不高的情况下具有较好的适用性,但该算法受噪声影响较大,容易导致定位结果发散。基于此发展的加权最小二乘算法(Weighted Least Squares,WLS)可以有效对抗噪声的影响,但定位结果容易陷入局部最优值。基于此,提出一种基于TDOA二次加权的QWLS定位算法,该算法可以大大降低噪声对定位的影响,并获取定位全局最优值,有较好的定位效果。同时探索了不同基站几何布局对不同算法定位精度的影响,通过改善基站几何布局使得QWLS算法有更高的定位精度。

At present,the least square method(LS),a TDOA based positioning algorithm,has good applicability in the case of low positioning accuracy requirements,whether indoors or outdoors.However,this algorithm is greatly affected by noise,which easily leads to divergence of positioning results.The weighted least squares algorithm(WLS)developed based on this can effectively resist the influence of noise,but the positioning result is easy to fall into the local optimal value.Based on this,it proposes a QWLS positioning algorithm based on TDOA quadratic weighting.This algorithm can greatly reduce the influence of noise on positioning and obtain the global optimal value of positioning,which has a good positioning effect.At the same time,it explores the impact of different geometric layouts of base stations on the positioning accuracy of different algorithms.By improving the geometric layout of base stations,the QWLS algorithm has higher positioning accuracy.