An Acoustic Network Navigation System

Abstract

This work describes a system for acoustic‐based navigation that relies on the addition of localization services to underwater networks. The localization capability has been added on top of an existing network, without imposing constraints on its structure/operation. The approach is based on the inclusion of timing information within acoustic messages through which it is possible to know the time of an acoustic transmission in relation to its reception. Exploiting such information at the network application level makes it possible to create an interrogation scheme similar to that of a long baseline. The advantage is that the nodes/autonomous underwater vehicles (AUVs) themselves become the transponders of a network baseline, and hence there is no need for dedicated instrumentation. The paper reports at sea results obtained from the COLLAB–NGAS14 experimental campaign. During the sea trial, the approach was implemented within an operational network in different configurations to support the navigation of the two Centre for Maritime Research and Experimentation Ocean Explorer (CMRE OEX) vehicles. The obtained results demonstrate that it is possible to support AUV navigation without constraining the network design and with a minimum communication overhead. Alternative solutions (e.g., synchronized clocks or two‐way‐travel‐time interrogations) might provide higher precision or accuracy, but they come at the cost of impacting on the network design and/or on the interrogation strategies. Results are discussed, and the performance achieved at sea demonstrates the viability to use the system in real, large‐scale operations involving multiple AUVs. These results represent a step toward location‐aware underwater networks that are able to provide node localization as a service.

A Comprehensive Survey of Recent Routing Protocols for Underwater Acoustic Sensor Networks

“…Location-based routing schemes require location estimates of sensor nodes to determine routes for data forwarding. Location estimation can be achieved using suitable localization services, such as those proposed in [12,13,14,15,16,17,18,19,20,21,22,23]. Table 1 analyzes these protocols based on a number of parameters explained in Section 1.…”

OCEANIDS: Building Next Generation Maritime Autonomous Systems

“…It encodes data to be transmitted from the vehicle. The communication module is also responsible for handling underwater communications as well as acoustic localization services (Munafo & Ferri, 2017). Local Node Health Monitor: All the sensor and actuator drivers in the vehicle implement a health reporting mechanism.…”

“…The performance of the TAN method is influenced by the quality of the available maps and by the morphology of the seabed (rougher terrains are more informative) as well as by the sensitivity of the bathymetric sensors to changes in the AUV pose (Meduna, 2011). The advantage of TAN with respect to more traditionally beacon-based acoustic methods (Hunt et al, 1974), (Munafo & Ferri, 2017), is that it does not need any external infrastructure, and it is hence particularly appealing for long-range AUV missions. The TAN algorithm developed for the ALR family of vehicles uses a Particle Filter (PF) to estimate the vehicle position.…”

Terrain‐aided navigation for long‐endurance and deep‐rated autonomous underwater vehicles

“…In such systems, an AUV localises itself by multilaterating acoustic ranges obtained from globally referenced transponders. Recent alternatives include: using an unmanned surface vehicle, which offers significant savings in expensive ship time (Pascoal et al, , ; Salavasidis, Harris, Rogers, & Phillips, ), a moving LBL (Curcio et al, ), or network‐supported navigation systems (Munafò & Ferri, ). In principle, positioning could be also achieved using single‐range measurements, either from a fixed or moving beacon.…”