While acoustic communications are still considered the most prominent technology to communicate under water, other technologies are being developed based, e.g., on optical and radio-frequency electromagnetic waves. Each technology has its own advantages and drawbacks: for example, acoustic signals achieve long communication ranges at order-of-kbit/s rates, whereas optical signals offer order-of-Mbit/s transmission rates, but only over short ranges. Such a diversity can be leveraged by multimodal systems, which integrate different technologies and provide the intelligence required to decide which one should be used at any given time. In this paper, we address a fundamental part of this intelligence by proposing Optimal Multimodal Routing (OMR), a novel routing protocol for underwater networks of multimodal nodes. OMR makes distributed decisions about the flow in each link and over each technology at any given time, in order to advance a packet towards its destination; in doing so, it prevents bottlenecks and allocates resources fairly to different nodes. We analyze the performance of OMR via simulations and in a field experiment. The results show that OMR successfully leverages all technologies to deliver data, even in the presence of imperfect topology information. To permit the reproduction of our results, we share our simulation code.

Accurate time synchronization of the nodes of digital underwater acoustic (UWA) networks is necessary for the effective use of information obtained from various kinds of underwater sensors over a vast water area. The sensors of autonomous underwater vehicles (AUV) are widely used to address new challenges. One of them is time synchronization of sensors on mobile carriers, as well as synchronization of the clocks on mobile nodes of UWA networks, for example, teams of AUVs that perform coordinated and/or cooperated operations. The paper presents theresults of the experiments on using UWA modems for AUV positioning, namely, UWA modems with chip-scale atomic clocks (CSAC) that allow accurate measurements of delays in propagation of UWA signals and, thus, accurate estimation of ranges to their georeferenced sources. In addition, the accuracy of CSAC operation in various situations as well as positioning accuracy of AUVs having UWA modems with integrated CSACs are analyzed based on the experimental results. Also given are practical recommendations on how to "discipline" (steer) CSACs and provide their phase synchronization with a source of timekeeping signals.

Underwater sensing and remote telemetry tasks necessitate the accurate geo-location of sensor data series, which often requires underwater acoustic arrays. These are ensembles of hydrophones that can be jointly operated in order to, e.g., direct acoustic energy towards a given direction, or to estimate the direction of arrival of a desired signal. When the available equipment does not provide the required level of accuracy, it may be convenient to merge multiple transceivers into a larger acoustic array, in order to achieve better processing performance. In this paper, we name such a structure an “array of opportunity” to signify the often inevitable sub-optimality of the resulting array design, e.g., a distance between nearest array elements larger than half the shortest acoustic wavelength that the array would receive. The most immediate consequence is that arrays of opportunity may be affected by spatial ambiguity, and may require additional processing to avoid large errors in wideband direction of arrival (DoA) estimation, especially as opposed to narrowband processing. We consider the design of practical algorithms to achieve accurate detections, DoA estimates, and position estimates using wideband arrays of opportunity. For this purpose, we rely jointly on DoA and rough multilateration estimates to eliminate spatial ambiguities arising from the array layout. By means of emulations that realistically reproduce underwater noise and acoustic clutter, we show that our algorithm yields accurate DoA and location estimates, and in some cases it allows arrays of opportunity to outperform properly designed arrays. For example, at a signal-to-noise ratio of –20 dB, a 15-element array of opportunity achieves lower average and median localization error (27 m and 12 m, respectively) than a 30-element array with proper λ / 2 element spacing (33 m and 15 m, respectively). We confirm the good accuracy of our approach via emulation results, and through a proof-of-concept lake experiment, where our algorithm applied to a 10-element array of opportunity achieves a 90th-percentile DoA estimation error of 4 ∘ and a 90th-percentile total location error of 5 m when applied to a real 10-element array of opportunity.

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The management of a heterogeneous mix of underwater vehicles needs a robust and reliable communication network, able to connect the remote command and control station (typically ashore or on board of a support ship) with nodes and vehicles in the deep sea. On the basis of this scenario, the infrastructure shall satisfy requirements such as: medium to extremely long distances between the control room and the area of operation; management of a variable number and type of nodes and vehicles (mobile, fixed, underwater, surfaced); a guaranteed bandwidth to send commands and receive platform status and tasks execution information with minimum latency; a high bitrate to transfer sensor data, pictures and videos in “near real time”; etc. Compared to the available solutions used nowadays for radio communication systems, the underwater environment imposes several constraints on the maximum achievable bandwidth and distance, drastically reducing data transfer rates. This means that the full communication network is a trade-off between different requirements and performances. The SWARMs project approach to this problem is to select, combine and integrate different and heterogeneous communication technologies, components and solutions, in order to obtain the best performances for the management and control of underwater vehicles during the execution of different missions and tasks. The network is mainly based on commercial components, but specific adaptations were made in order to fulfil the requirements of ad hoc underwater and overwater sub networks in maritime specific scenarios. Several experiments and sea trials have allowed the verification of the performance of the full network and the optimization of its configuration according to the mission needs.