Multi-path Penalty Metric in Underwater Acoustic Communication for Autonomy and Human Decision-making

A novel performance metric to improve underwater digital acoustic communication, called Multipath Penalty (MPP), is proposed as an alternative to traditional signal-to-noise ratio (SNR) methods in the context of the Arctic Beaufort Sea. MPP and SNR are compared alongside a third performance metric, Minimum Achievable Error (MAE), which replicates the operation of a channel estimate-based decision feedback equalizer in an acoustic modem. The three metrics are then tested in a hardware-in-the-loop Virtual Ocean simulator for an autonomous undersea vehicle (AUV) communicating with a collaborator. Using field data of modem statistics obtained during ICEX20 and expanding data supplied by the simulator, calibration of the three metrics to modem packet success is evaluated, resulting in proposed recalibration for MAE. The AUV's ability to communicate when adaptively choosing its depth is analyzed above and below the Beaufort Lens, and settings for MPP's engineering variables are obtained. The results show MPP generally improves reception and demodulation of acoustic transmissions over SNR by approximately 5% within an operational range of 8 km, while achieving similar results to the more robust metric MAE. MPP is an improved utility for underwater digital acoustic communication in both marine autonomy and as a tactical decision aid.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Howard, Bradli Anne

Advisor dc:contributor.advisor

• Schmidt, Henrik

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/140080

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/140080