Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments

Abstract

Deploying long-range autonomous underwater vehicles (AUVs) mid-water column in the deep ocean is one of the most challenging applications for these submersibles. Without external support and speed over the ground measurements, dead-reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and lowpower terrain-aided navigation (TAN) system is developed. A Rao-Blackwellized Particle Filter robust to estimation divergence is designed to estimate the vehicle's position and the speed of water currents. To evaluate performance, field data from multiday AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low-power sensors and a Doppler velocity log to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100, 200, and 400 m resolution are generated by subsampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, the results of this study suggest that TAN can enable AUV operations of the order of months using global bathymetric models.

Terrain-Aided Navigation With Coarse Maps—Toward an Arctic Crossing With an AUV

“…In contrast to the above, it was demonstrated in Salavasidis, et al [33] that the TAN system of the ALR vehicles can deal with low-quality bathymetric grid maps and strong time-varying water currents, despite using basic low-power sensors. The performance of the navigation system was evaluated using field data collected during three multi-day deployments of the ALR6000 in the Southern Ocean (with the longest mission, named M44 and shown in Fig.…”

“…These platforms combine the extreme range already achievable by underwater gliders [32] with increased manoeuvrability, position control and payload capacity of large flight-style AUVs. By using high energy density lithium primary cells and minimising the energy consumption within all sub-systems, the vehicles can achieve a multi-month endurance [33], [34]. This capability coupled with the ample flooded space available and the increasing availability of low-power sensors have provided these vehicles with a variety of payload options and use cases.…”

“…This problem further escalates during missions in extremely high latitudes, where heading sensors experience degraded performance [23], [33], and/or whilst operating mid-water column where the navigation that is influenced by water currents is presently the weakest [36].…”

“…To enable long-range missions under the sea ice with the ALR vehicles, a terrain-aided navigation (TAN) system has been developed providing a computationally feasible solution in real-time on processing boards with limited resources [34], [37], [38]. The system relies on basic low-power motion sensors and low-informative sonars to obtain bathymetric observations, such as the NOC's single-beam echo-sounder specifically developed and optimised for the ALR1500.…”

Topographic SLAM Using a Single Terrain Altimeter in GNSS-Restricted Environment

“…Although not as established as in aerospace applications, there has been some research on TRN using bathymetric information in marine applications for underwater vehicles [5]- [9]. A survey paper by Carreno et al [10] compared several mathematical filter models for TRN techniques for autonomous underwater vehicles (AUVs) with a description of the original TERCOM algorithm.…”