GNSS-A Network Solution with Zenith Acoustic Delay Estimation

Abstract

The ocean sound speed changes drastically with time and space. It is almost impossible to achieve centimeter-level-precision Global Navigation Satellite System (GNSS)-Acoustic (GNSS-A) positioning without regarding spatio-temporal variations of sound speed. Inspired by the atmospheric delay estimation, we define zenith acoustic delay (ZAD) as the zenith-direction ranging error sourced by the sound speed variations, and then it is decomposed into one temporal component and two horizontal components for the sound speed variations in time and space, respectively. We propose a network solution with the three ZAD components of each seafloor geodetic point as common parameters to be estimated, and then present a piece-wise estimation to characterize their time-varying nature. To remedy the ray bending effect this study is implemented in the context of the ray tracing algorithm based on a reference sound speed profile (SSP). Experimental tests show that the proposed network solution improves ZAD estimation and results in a better position determination as compared to the single-point positioning (SPP) solution. The proposed network solution for a single campaign can achieve a horizontal positioning precision better than 5 cm (1-sigma) for the seafloor geodetic array centroid. The temporal variation of ZAD is up to one meter while the horizontal variations vary within a few decimeters in the time domain and show an azimuthal asymmetry in space.

Keywords:

• Seafloor geodesy
• GNSS-A
• ray tracing
• acoustic delay
• network solution
• mapping function

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Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

We are very grateful to Hydrographic and Oceanographic Department, Japan Coast Guard providing open seafloor geodetic data for this paper. All experimental data can be obtained through the open-source website https://www1.kaiho.mlit.go.jp/KOHO/chikaku/kaitei/sgs/datalist.html

Additional information

Funding

It is also partially supported by National Natural Science Foundation of China (No. 41931076). This study was supported by the LaoShan project (–> LSKJ202205100, LSKJ202205105). This study was supported by the National Key Research and Development Program of China (No. 2020YFB0505802).