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

<jats:p> 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, computational...

Full description

Bibliographic Details
Main Authors: Bhatt, EeShan C, Viquez, Oscar, Schmidt, Henrik
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article in Journal/Newspaper
Language:English
Published: Acoustical Society of America (ASA) 2022
Subjects:
Online Access:https://hdl.handle.net/1721.1/145518
Description
Summary:<jats:p> 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. </jats:p>