Vehicle localization integrity based on trajectory monitoring
Vehicle localization integrity based on trajectory monitoring
复制标题
基于轨迹监测的车辆定位完整性
DOI：
10.1109/iros.2009.5354156
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
D. Bétaille
中科院分区：
文献类型：
--
作者：
Olivier Le;P. Bonnifait;J. Guzman;D. Bétaille
移动机器人要实现自主导航，确定自己的位置是至关重要的。然而，当在复杂的户外环境中操作时，这是困难的，并且通常结果是不准确的。为了保证位置估计的确定性，采用了完整性的概念。这是对提供保证位置区域的信心程度的度量。该过程包括使用故障检测和排除（FDE）算法去除测量中的异常值，然后计算量化完整性区域的保护级别（PL）。这主要适用于航空航天领域的全球导航卫星系统（GNSS），该领域存在数据冗余且多路径较少，而陆地应用则不是这样。本文提出了一种陆地移动机器人定位完整性的新方法，该方法将车辆和GNSS数据结合起来，存储在短期记忆中，即数据视界中。该公式允许在组合数据集上应用FDE算法。它还会导致冗余的增加，从而减少PLs并增加完整性算法的可用性。
For mobile robots to navigate autonomously, knowing with certainty their location is fundamental. However, this is difficult when operating in complex outdoors environments, and often results are inaccurate. To guarantee the certainty of the location estimates, the notion of integrity is used. This is a measure of the degree of confidence that provides a guaranteed location zone. The process consists in removing outliers amongst the measurements using Fault Detection and Exclusion (FDE) algorithms and then to compute Protection Levels (PL) that quantify the integrity zone. This is applicable mainly to Global Navigation Satellite Sytems (GNSS) in the aerospace domain where data redundancy exists and few multipath, which is not the case for land applications. In this paper, a new approach to localization integrity for land mobile robots is proposed by combining vehicle and GNSS data, stored within a short-term memory, the data horizon. This formulation allows for the application of FDE algorithms on the combined data set. It also leads to a gain of redundancy that enables PLs to be reduced and to increase the availability of integrity algorithms.