基于精确红外-超宽带距离测量的gnss辅助vanet协同定位

Gia-Minh Hoang, B. Denis, Jérôme Härri, D. Slock
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引用次数: 25

摘要

基于脉冲无线电-超宽带(IR-UWB)的协同定位在锚节点位置完全已知的情况下,可以提供厘米级的精度。在车辆自组织网络(VANETs)中,作为“虚拟锚”节点的车辆具有高度的移动性,并且全球导航卫星系统(GNSS)提供的位置估计不完美。GNSS定位测量噪声与IR-UWB车对车(V2V)测距测量噪声之间存在较大差异,会在定位滤波器中产生偏置,这种偏置会协同传播给其他车辆,从而显著削弱IR-UWB协同定位(CLoc)的优势。本文提出了一种新的两步CLoc融合框架来弥补这一缺陷。它首先选择GNSS位置不确定性最低的“虚拟锚”节点来减轻和阻止偏差的传播。一旦所有的偏差都减少了,它就会通过穷极融合来提高定位精度。该策略将40厘米精度从25%(传统IR-UWB)提高到95%的概率,甚至将20厘米精度从5%提高到40%的概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative localization in GNSS-aided VANETs with accurate IR-UWB range measurements
Cooperative positioning based on Impulse Radio — Ultra WideBand (IR-UWB) is known to provide a centimeter-level accuracy when the positions of anchor nodes are perfectly known. In Vehicular Ad-Hoc Networks (VANETs), vehicles acting as “virtual anchor” nodes are highly mobile with imperfect position estimates delivered by the Global Navigation Satellite System (GNSS). The large difference between measurement noises of GNSS positioning and IR-UWB Vehicle-to-Vehicle (V2V) ranging creates a bias in the localization filter, which is cooperatively propagated to other to other vehicles, and therefore significantly attenuates the benefits of IR-UWB for Cooperative Localization (CLoc). This paper compensates this drawback by a novel 2-step CLoc fusion framework. It first selects the “virtual anchor” nodes with the lowest GNSS position uncertainty to mitigate and stop the propagation of the biases. Once all biases have been reduced, it refines localization accuracy through exhaustive fusion. This strategy increases the probability to reach a 40 cm accuracy from 25% (conventional IR-UWB) to 95%, and even a 20 cm accuracy from 5% to 40%.
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