Under-ice acoustic navigation using real-time model-aided range estimation

Abstract

The long baseline (LBL) underwater navigation paradigm relies on the conversion of travel times into pseudoranges to trilaterate position. For real-time autonomous underwater vehicle (AUV) operations, this conversion assumes an isovelocity sound speed. For re-navigation, computationally and/or labor-intensive acoustic modeling may be employed to reduce uncertainty. This work demonstrates a real-time ray-based prediction of the effective sound speed along a path from source to receiver. This method was implemented for an AUV-LBL system in the Beaufort Sea in an ice-covered and a double-ducted propagation environment. Given the lack of Global Navigation Satellite Systems (GNSS) data throughout the vehicle's mission, the pseudorange performance is first evaluated on acoustic transmissions between GNSS-linked beacons. The mean real-time absolute range error between beacons is roughly 11 m at distances up to 3 km. A consistent overestimation in the real-time method provides insights for improved eigenray filtering by the number of bounces. An operationally equivalent pipeline is used to reposition the LBL beacons and re-navigate the AUV, using modeled, historical, and locally observed sound speed profiles. The best re-navigation error is 1.84 ± 2.19 m root mean square. The improved performance suggests that this approach extends the single meter accuracy of the deployed GNSS units into the water column.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 01, 2022
Source ID
10.1121/10.0010260

Entities

People

  • EeShan Bhatt
  • Henrik Schmidt
  • Oscar A. Víquez

Organizations

  • Massachusetts Institute of Technology
  • Office of Naval Research

Tags

Readers

  • Positioning, Navigation, and Timing (PNT) Technology.
  • Regression Analysis.
  • Wave Propagation and Nonlinear Chaotic Dynamics.

Technology Areas

  • Space