3D Ensemble-Based Online Oceanic Flow Field Estimation for Underwater Glider Path Planning

TL;DR

This paper introduces a 3D ensemble-based estimator for ocean flow fields that significantly improves accuracy over traditional 2D methods, aiding underwater glider navigation.

Contribution

It extends previous 2D flow estimation techniques to 3D using ensemble forecasts and iterative updates, reducing navigation errors in autonomous marine vehicles.

Findings

Lower error metrics in flow estimation compared to existing methods.

Effective in both noisy and noise-free measurement scenarios.

Demonstrated with real ensemble forecasts and synthetic data.

Abstract

Estimating ocean flow fields in 3D is a critical step in enabling the reliable operation of underwater gliders and other small, low-powered autonomous marine vehicles. Existing methods produce depth-averaged 2D layers arranged at discrete vertical intervals, but this type of estimation can lead to severe navigation errors. Based on the observation that real-world ocean currents exhibit relatively low velocity vertical components, we propose an accurate 3D estimator that extends our previous work in estimating 2D flow fields as a linear combination of basis flows. The proposed algorithm uses data from ensemble forecasting to build a set of 3D basis flows, and then iteratively updates basis coefficients using point measurements of underwater currents. We report results from experiments using actual ensemble forecasts and synthetic measurements to compare the performance of our method to the direct 3D extension of the previous work. These results show that our method produces estimates with dramatically lower error metrics, with and without measurement noise.