Metering Method and Measurement Uncertainty Evaluation of Underwater Positioning System in Six Degrees of Freedom Space

Abstract

Meterage is an important action to ensure the performance of underwater acoustic positioning system, but the commonly used measurement methods are mostly based on the low degrees of freedom (DOF) measurement and control platforms which could not realize the all-round and high efficiency evaluation of this equipment. In this paper, we develop a new metering method base on the conventional standard 4-DOF measurement and control platform to realize the whole exploration space high efficiency and high accuracy measurement of underwater acoustic positioning systems in 6-DOF space. First, a 4-DOF space to 6-DOF space quantity value propagation model is proposed, and a rigorous mathematical expression is established. Next, a measurement procedure is formed based on the building of a standard base-line field, so the channel of transforming measurable position coordinate of the measured field point in 4-DOF space to the 6-DOF space is established. Finally, the evaluation of the measurement uncertainty is done using both the Guide to the expression of uncertainty in measurement method (GUM method) and Adaptive Monte Carlo method (AMCM method), and the evaluation results of GUM method are verified by AMCM method correspondingly, the effectiveness of this metering theory and the corresponding uncertainty evaluation methods are also illustrated by analyzing the length of coverage interval and numerical tolerances of measurement uncertainty. The research results show that the relative combined uncertainty of the metering system is not higher than 0.18% with the parameters given in this paper. INDEX TERMS Metering method, measurement uncertainty evaluation, quantity value propagation model, 6-DOF space, underwater acoustic positioning system.

Analyzing Impact of Data Uncertainty in Distributed Energy Resources using Bayesian Networks

“…In [8], the concept of geosensors was introduced to model and predict the sensor data uncertainty for the environmental monitoring applications. In [9], authors proposed the guide to the expression of measurement uncertainty and Adaptive Monte Carlo method, to analyze the measurement uncertainty in underwater positioning systems. However, the uncertainty evaluation in DERs requires higher data granularity to identify the real-time data variations, in which the existing methods would fail [3]- [5], [8], [9].…”