Acoustic propagation in the Beaufort Sea is particularly sensitive to upper-ocean sound-speed structure due to the presence of a subsurface duct known as the Beaufort duct. Comparisons of acoustic predictions based on existing Arctic models with predictions based on in situ data collected by Seaglider vehicles in the summer of 2017 show differences in the strength, depth, and number of ducts, highlighting the importance of in situ data. These differences have a significant effect on the later, more intense portion of the acoustic time front referred to as reverse geometric dispersion, where lower-order modes arrive prior to the final cutoff.

This paper describes an acoustic navigation system that provides mesoscale coverage (hundreds of kilometers) under the ice and presents results from the first multi-month deployment in the Arctic. The hardware consists of ice-tethered acoustic navigation beacons transmitting at 900 Hz that broadcast their latitude and longitude plus several bytes of optional control data. The real-time under-ice navigation algorithm, based on a Kalman filter, uses time-of-flight measurements from these sources to simultaneously estimate vehicle position and depth-averaged local currents. The algorithm described herein was implemented on Seagliders, a type of autonomous underwater glider (AUG), but the underlying theory is applicable to other autonomous underwater vehicles (AUVs). As part of an extensive field campaign from March to September 2014, eleven acoustic sources and four Seagliders were deployed to monitor the seasonal melt of the marginal ice zone (MIZ) in the Beaufort and northern Chukchi Seas. Beacon-to-beacon performance was excellent due to a sound duct at 100 m depth where the transmitters were positioned; the travel-time error at 200 km has a standard deviation of 40 m when sound-speed is known, and ranges in excess of 400 km were obtained. Results with the Seagliders, which were not regularly within the duct, showed reliable acoustic ranges up to 100 km and more sparse but repeatable range measurements to over 400 km. Navigation results are reported for the real-time algorithm run in post-processing mode, using data from a 295-hour segment with significant time spent under ice.

This paper presents an under-ice acoustic navigation system developed for Seaglider, a buoyancy-driven autonomous underwater vehicle (AUV), and post-processed navigation results from one of fourteen glider deployments between 2006 and 2014 in Davis Strait. Seagliders typically receive all geolocation information from global positioning system (GPS) signals received while they are at the surface, and perform dead reckoning while underwater. Extended under-ice deployments, where access to GPS is denied due to the inability of the glider to surface, require an alternative source of geolocation information. In the deployments described herein, geolocation information is provided by range measurements from mooring-mounted acoustic navigation sources at fixed, known locations. In this paper we describe the navigation system used in Davis Strait and present navigation results from a six degree-of-freedom Kalman filter using post-processed navigation data.