Diba Mirza

Motion-aware self-localization for underwater networks

A myriad of ocean processes affect life on the planet and are a source of intrigue to oceanographers and scientists. Understanding these processes and their interactions with currents requires collection of relevant data. A network of mobile platforms can be used to learn the correlation of processes in space and over time. To do this, data samples collected by nodes have to be annotated with location information. Given limited access to Global Positioning Systems underwater, collaborative self-localization schemes applied periodically are well-suited for this purpose. However, the specific nature of the underwater acoustic environment introduces significant error during network self-localization due to the combined effect of large latencies in communication and node mobility. We propose a method to account for these effects thus significantly improving the accuracy of position estimates.

D-sync: Doppler-based time synchronization for mobile underwater sensor networks

Time synchronization is an essential service in underwater networks, required for many functionalities such as MAC, sleep-scheduling, localization, and time-stamping of sensor events. However, there exist two fundamental challenges to underwater synchronization, namely, large propagation delays and substantial node mobility during the synchronization process. While existing underwater time sync solutions have been proposed to address these challenges, they rely on heavy signaling, which is undesirable due to high energy costs. In this paper, we introduce a powerful new approach that incorporates physical layer information, namely an estimate of the Doppler shift. Large Doppler shift has been identified as a major challenge to underwater communication, and current systems implement sophisticated solutions to estimate and track such Doppler shift for each data exchange. While an impediment to communication, we will show that the Doppler shift contains highly useful information that can be leveraged to greatly improve time synchronization. Specifically, it provides an indication of the relative motion between nodes. Our new protocol, called D-sync, strategically exploits this feature to address the timing uncertainty due to node mobility. As such, D-sync can handle substantial mobility, without making any assumptions about the underlying motion, and without extensive signaling. Simulation results show that D-sync significantly outperforms existing time synchronization both in terms of accuracy and energy.

Designing an Adaptive Acoustic Modem for Underwater Sensor Networks

There is a growing interest in using underwater networked systems for oceanographic applications. These networks often rely on acoustic communication, which poses a number of challenges for reliable data transmission. The underwater acoustic channel is highly variable; each link can experience vastly different conditions, which change according to environmental factors as well as the locations of the communicating nodes. This makes it difficult to ensure reliable communication. Furthermore, due to the high transmit power, the energy consumed in transmitting data is substantial, which is exacerbated at lower data rates. The main challenge that we address in this article is how to build a system that provides reliable and energy efficient communication in underwater sensor networks. To this end, we propose an adaptive underwater acoustic modem which changes its parameters according to the situation. We present the design of such a modem and provide supporting results from simulations and experiments.

Collaborative Localization for Fleets of Underwater Drifters

A crucial goal for ocean-sensing systems is to obtain spatially-rich data that allows us to understand the correlations between ocean processes. To achieve this, we consider a system consisting of swarms of underwater drifters that float freely with currents and therefore achieve high spatial sampling of the ocean. Our goal is to ensure that this system is self-organizing and autonomous which is key for practical large-scale deployments in remote regions. We consider a crucial aspect of data collection, namely, determining the locations at which data was sensed. Given our overall design goal, we propose a localization strategy where nodes collaborate to determine their positions autonomously without using long range transponders on surface buoys or ships. This in turn significantly impacts the cost and ease of deployment of such systems. Further, we determine optimum configurations for the swarm so that their position estimation error is minimized.

Energy-Efficient Ranging for Post-Facto Self-Localization in Mobile Underwater Networks

Many ocean processes, both biological and physical, greatly depend on and interact with the intrinsic current dynamics of the underwater environment. A promising approach to understand small and large scale spatio-temporal correlations of these processes is to deploy a networked swarm of drifters that float freely with ocean currents. They form a coordinated distributed sampling system that observes ocean processes within their own moving frame of reference. As data interpretation is impossible without knowledge of sampling positions, a method is required to localize the drifters. Furthermore, the localization has to be repeated periodically as the network topology changes due to the inherent motion of the vehicles. This paper proposes a novel energy-aware, distributed solution based on inter-drifter range measurements. It leverages the realization that actual position estimation can be performed after the mission is over. The proposed broadcast-based solution achieves sufficient localization accuracy with an extremely low overhead: around 0.5 transmissions per node per localization.

Energy-efficient wakeup scheduling for maximizing lifetime of IEEE 802.15.4 networks

Deployment of wireless ad hoc networks with scarce energy resources necessitates the design of algorithms that maximize the lifespan of the network, sustain connectivity and facilitate easy maintenance. Nodes in an ad hoc network often need to collaborate with each other to maintain network-connectivity or execute a set of tasks in a distributed fashion. They may have variable rates of energy consumption because some nodes perform energy-intensive tasks such as data-aggregation and data-forwarding more than others. These variations cause early energy depletion of certain nodes which impacts both the connectivity and the overall lifetime of the network. In this paper, we propose a scheme that alleviates this problem in low-traffic networks by tuning the energy consumption of a node during periods of inactivity to its energy-expenditure in the active phase. Since nodes are idle for extended periods of time, this compensation proves significant and we show that the lifetime of an IEEE 802.15.4 network improves up to 65% while ensuring that an end-to-end delay constraint is met.

Real-time collaborative tracking for underwater networked systems

Localization is a crucial requirement for mobile underwater systems. Real-time position information is needed for control and navigation of underwater vehicles, in early warning systems and for certain routing protocols. Past research has shown that the localization accuracy of networked underwater systems can be significantly improved using collaborative tracking techniques. More specifically the Maximum Likelihood (ML) position estimates of a mobile collective can be computed from measurements of relative positions and motion, albeit centrally and non-real time. While for a number of underwater applications non-real-time position estimates may suffice, in this paper we focus on the design of a collaborative tracking solution that operates in real-time, yet is scalable and energy-efficient. Using the ML solution as a baseline, we identify key factors that fundamentally limit the performance of real-time (centralized and distributed) solutions, quantifying their effects via simulations. In the remaining solution space, we propose a low overhead scheme for real-time and distributed tracking. The specific challenges that we address include determining what information should be shared between vehicles, how this information must be encoded to minimize the communication overhead and when should vehicles communicate with each other to achieve the best performance with the minimum energy consumption. Our proposed technique can strategically trade off localization accuracy and energy consumption, achieving more than 50% reduction in the communication overhead compared to any fixed scheme.

Collaborative tracking in mobile underwater networks

A key requirement of underwater sensing systems is to track the position of devices while submerged. Traditionally, such tracking has relied on inertial navigation units and acoustic range measurements with surface beacons to estimate node positions over time. While effective for small clusters of instruments, these approaches do not scale well when underwater systems become truly networked. Instead, networked instruments can rely on collaborative localization techniques. However, as these only estimate node positions for time snapshots of the network, this solution breaks down in sparse deployments. In this paper we propose an innovative new approach, collaborative tracking, that marries the benefits from both existing solutions, while overcoming their disadvantages. Our scheme provides complete 4D trajectory estimation, leveraging both time and spatial dimensions, and operates well into regions where both surface beacons and network connectivity are sparse.

A swarm of autonomous miniature underwater robot drifters for exploring submesoscale ocean dynamics

Measuring the ever-changing 3-dimensional (3D) motions of the ocean requires simultaneous sampling at multiple locations. In particular, sampling the complex, nonlinear dynamics associated with submesoscales (<1–10 km) requires new technologies and approaches. Here we introduce the Mini-Autonomous Underwater Explorer (M-AUE), deployed as a swarm of 16 independent vehicles whose 3D trajectories are measured near-continuously, underwater. As the vehicles drift with the ambient flow or execute preprogrammed vertical behaviours, the simultaneous measurements at multiple, known locations resolve the details of the flow within the swarm. We describe the design, construction, control and underwater navigation of the M-AUE. A field programme in the coastal ocean using a swarm of these robots programmed with a depth-holding behaviour provides a unique test of a physical–biological interaction leading to plankton patch formation in internal waves. The performance of the M-AUE vehicles illustrates their novel capability for measuring submesoscale dynamics.

ToA-TS

Time synchronization and localization are key requirements for distributed underwater systems consisting of numerous low-cost submersibles. In these systems, submersibles are highly resource constrained and typically have limited acoustic communication capability. We investigate the problem of tracking submersibles that only have the capability of receiving acoustic signals. Traditional Long Base Line (LBL) systems track the location of submersibles by providing a GPS-like infrastructure that consists of a few reference beacons at known locations. In these systems the unknown positions of submersibles are estimated from beacon transmissions using time-difference-of-arrival (TDoA) based localization. As such TDoA makes the key assumption that beacon transmissions occur nearly concurrently in time. While this assumption is ensured in small LBL deployments it does not hold as the size of the system scales up. In this paper we identify scenarios where signals from multiple beacons are significantly lagged in time. We further identify the motion of the submersible between signal arrivals as a key factor that deteriorates the performance of TDoA, when transmissions are not concurrent. To address this problem we propose to track the submersible while performing time-synchronization. Our proposed technique, called Time of Arrival based Tracked Synchronization (ToA-TS) essentially extends GPS like localization for scenarios where beacon transmissions are not concurrent and submersibles are not capable of two-way communication. We show the benefit of our proposed scheme by comparing its performance to other localization techniques using experimentally obtained data.