基于小波分析除噪的全质心UWB室内定位研究

Research of UWB indoor Location Based on Wavelet Analysis and Full Centroid Position Scheme

为了解决室内环境下的非视距(non-line-of-sight,NLOS)及多径(Multipath)传播问题给定位精度带来较大误差的问题,为提高定位精度首先将通过超宽带(ultra wideband,UWB)室内定位系统中的TOA模型测得的目标节点(携带定位终端的人或物体)分别到三个锚节点(下位机)的距离值进行小波分析除噪,再运用三角形全质心定位算法对目标节点进行最终定位(求出目标节点在二维坐标系中的坐标值)。仿真结果表明,改进算法明显提高了定位精度,并且比传统的粒子滤波法,贝叶斯滤波法,泰勒级数法等提高定位精度的算法更加简洁,免去了测试大量数据的过程,从而具有较强的实时性,避免了泰勒级数法因定位结果的初值选取不当而不收敛的鲁棒性较弱的弊端,证明提出的优化TOA测距方案具有更高的可行性。

This theis aims to avoid big errors caused by the NLOS and muhipath transmission in indoor environ- ment when determining the position of an object or person. In order to improve positional accuracy ,the author propo- ses that firstly use Wavelet analysis to denoise, which is conducted by measuring the distance between target nodes （object or person with positioning terminal ） and three anchor nodes （lower computer） obtained by TOA model of UWB Indoor Positioning System. Then determine the final location of target nodes by adopting Full Centroid Position scheme, namely finding the coordinate values of the target nodes in two - dimensional coordinate system. Simulation results indicate that the above method has the advantage of possessing higher positional accuracy and less data testing compared with traditional particle filter, Bayesian filter method and Taylor Series Approach, thus having better real - time. This method can avoid the defects of weak non - convergence robustness caused by improper initial positional results when using Taylor Series Approach. It is proved that the advanced TOA model has more feasibility.