一种新颖的基于偏度的非视距区分算法  

A Novel Non-Line-of-Sight Identification Algorithm Based on Skewness

作　　者：张浩[1,2] 梁晓林[1] 吕婷婷[1] 徐凌伟[1] 

机构地区：[1]中国海洋大学信息科学与工程学院,山东青岛266100 [2]加拿大维多利亚大学电子与计算机工程学院,维多利亚V8W 3P6

出　　处：《电讯技术》2015年第5期484-490,共7页Telecommunication Engineering

基　　金：国家自然科学基金资助项目(60902005);青岛市国际科技合作项目(12-1-4-137-hz)~~

摘　　要：在超宽带(UWB)定位系统中,非视距(NLOS)传播是降低通信与定位精度可靠性的主要原因。因此,区分NLOS环境对提高定位精度尤为重要。针对该问题,提出了一种新的基于信道统计特性——偏度(Skewness)的NLOS区分算法。该算法首先将偏度在IEEE 802.15.4a信道模型(特别是室内家居和办公环境)中建模为对数正态分布,然后对其概率密度函数(PDF)做似然比检验来区分视距(LOS)与NLOS环境。仿真结果表明:室内UWB定位系统中,偏度可以更好地区分信道状态,在室内办公环境中,正确区分NLOS环境的概率可达99.99%。在定位模块中融入所获得的区分NLOS的结果将有助于定位精度的进一步提升。Non-line-of-sight（ NLOS） propagation can severely degrade the reliability of communication and localization accuracy in indoor ultra-wide-band（ UWB） positioning systems. It was important to dis-tinguish NLOS for positioning precision. For this problem,a novel NLOS identification technique based on skewness is proposed,which is one of the channel statistics. The IEEE 802. 15. 4a channel models are employed for simulation. Skewness can be well modelled as a log-normal distribution especially in the indoor and office environments. Subsequently, a likelihood ratio test for Probability Density Function （ PDF） is used to identify LOS/NLOS. The simulation results show that skewness can better distinguish the channel state with up to 99 . 99 percent accuracy on the quiz responses in the indoor office environ-ments. Localization accuracy is expected to be improved by incorporating the NLOS identification results into the positioning module.

关 键 词：室内定位 超宽带 非视距区分 信道统计特性 偏度 定位精度 

分 类 号：TN925[电子电信—通信与信息系统]