Equivalent Construction of 4-Dimensional Sound Speed Structure and Correction of Resilient Systematic Error for Improving GNSS-Acoustic Seafloor Positioning | IEEE Journals & Magazine | IEEE Xplore

Equivalent Construction of 4-Dimensional Sound Speed Structure and Correction of Resilient Systematic Error for Improving GNSS-Acoustic Seafloor Positioning


Abstract:

Global navigation satellite system-acoustic (GNSS-acoustic) seafloor positioning is essential for navigation, oil exploration and disaster forecast based on underwater Ac...Show More

Abstract:

Global navigation satellite system-acoustic (GNSS-acoustic) seafloor positioning is essential for navigation, oil exploration and disaster forecast based on underwater Acoustic Internet of Things Networks (UAIoTNs). The accuracy of this positioning is closely linked to the sound speed structure. In this work, we develop a two-stage compensation scheme for systematic errors to enhance GNSS-acoustic seafloor positioning and analyze the relationship between sound speed disturbance components and actual positioning. Firstly, we construct the travel time observation equation based on equivalent construction of the 4-dimensional sound speed structure that accounts for horizontal gradient. Additionally, we convert the systematic error of the travel time observation equation into a compensation term for the pseudorange equation. Building on this, we design a resilient inversion method to address various systematic error terms. The proposed positioning scheme are applied to real GNSS-acoustic seafloor observation data. The experiment results show that the systematic error compensation caused by the equivalent construction of the 4-dimensional sound speed structure largely covers the systematic error compensation caused by resilient terms. The actual positioning error of the two-stage scheme reaches the centimeter level in all directions, with horizontal and vertical positioning errors reduced by 39% and 68%, respectively, compared to not accounting for systematic errors.
Published in: IEEE Internet of Things Journal ( Early Access )
Page(s): 1 - 1
Date of Publication: 17 February 2025

ISSN Information:

Funding Agency:


Contact IEEE to Subscribe