WPI精密人员定位器:逆合成阵列和解层析成像

A. Cavanaugh, M. Lowe, D. Cyganski, R. J. Duckworth
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引用次数: 3

摘要

本文介绍了伍斯特理工学院(WPI)精确人员定位(PPL)项目正在开发的最新算法。我们的目标是生产一种可快速部署的临时系统,该系统可以在使用可用频谱的任何类型的应急响应场景中实现亚米级定位精度;我们特别希望找到建筑物内及周围的急救人员。先前的工作[1]导致了分离或松散耦合的方法来融合射频和惯性定位数据,以及来自其他传感器的数据。逆合成阵列调和层析成像(is - art)算法是射频和惯性测量的融合,与以前的系统有本质的不同。我们使用惯性位移来相干地融合连续的射频捕获,而不是融合定位结果。这种方法的好处是双重的。首先,融合仅依赖于小时间间隔的惯性值之间的关系,因此我们不会积累大的惯性漂移误差。其次,由于高多径环境对空间扰动非常敏感,因此每个点的射频条件预计会非常不同。由于多路径信号成分随着位置的变化而迅速变化,我们预计只有直接路径信号将在从独特位置捕获的连续RF数据之间相关联。为了使来自不同位置的直接路径信号相互关联,这些捕获必须对齐以与惯性位移数据融合。ISART算法执行这种信号对齐,并使用奇异值阵列调和层析成像(σART)算法[2]所采用的样本处理来计算基于这种直接路径相关性的度量;ISART解是度规最大的点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WPI precision personnel locator: Inverse synthetic array reconciliation tomography
This paper describes the latest algorithm being developed by the Worcester Polytechnic Institute (WPI) Precision Personnel Location (PPL) project. Our goal is to produce a rapidly deployable, ad-hoc system that can achieve sub meter positioning accuracy in any type of emergency response scenario using available spectrum; specifically we wish to locate first responders in and around buildings. Previous work [1] has led to separate or loosely coupled approaches for fusing RF and inertial positioning data, as well as data from other sensors. The Inverse Synthetic Array Reconciliation Tomography (IS-ART) algorithm is a fusion of RF and inertial measurements that is fundamentally different from previous systems. Instead of fusing positioning results, we use the inertial displacements to coherently fuse successive RF captures. The benefits of this approach are twofold. First, the fusion depends only on relationships between inertial values spanning small time intervals, so that we do not accumulate large inertial drift errors. Second, the RF conditions at each point are expected to be very different because high multi-path environments are very sensitive to spatial perturbations. Since the multi-path signal components are changing rapidly with position we expect that only the direct path signals will be correlated between successive RF data captures taken from unique positions. In order for the direct path signals from different locations to be correlated these captures must be aligned for fusion with the inertial displacement data. The ISART algorithm performs this signal alignment and computes a metric based on this direct path correlation using the sample processing employed by the Singular Value Array Reconciliation Tomography (σART ) algorithm [2]; the ISART solution is the point where the metric is maximal.
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