Thesis (Ph. D.)--University of Rhode Island, 2003. / Typescript. Includes bibliographical references (leaves 148-152).

Thesis (M.S. in Electrical Engineering and M.S. in Applied Physics)--Naval Postgraduate School, June 2005. / Thesis Advisor(s): Joseph Rice, Roberto Cristi. Includes bibliographical references (p. 117-119). Also available online.

In this dissertation, we propose decentralized and scalable algorithms for Gaussian process (GP) training and prediction in multi-agent systems. The first challenge is to compute a spatial field that represents underwater acoustic communication performance from a set of measurements. We compare kriging to cokriging with vehicle range as a secondary variable using a simple approximate linear-log model of the communication performance. Next, we propose a model-based learning methodology for the prediction of underwater acoustic performance using a realistic propagation model. The methodology consists of two steps: i) estimation of the covariance matrix by evaluating candidate functions with estimated parameters; and ii) prediction of communication performance. Covariance estimation is addressed with a multi-stage iterative training method that produces unbiased and robust results with nested models. The efficiency of the framework is validated with simulations and experimental data from field trials. The second challenge is to perform predictions at unvisited locations with a team of agents and limited inter-agent information exchange. To decentralize the implementation of GP training, we employ the alternating direction method of multipliers (ADMM). A closed-form solution of the decentralized proximal ADMM is provided for the case of GP hyper-parameter training with maximum likelihood estimation. Multiple aggregation techniques for GP prediction are decentralized with the use of iterative and consensus methods. In addition, we propose a covariance-based nearest neighbor selection strategy that enables a subset of agents to perform predictions. Empirical evaluations illustrate the efficiency of the proposed methods / Doctor of Philosophy / In this dissertation, we propose decentralized and scalable algorithms for collaborative multiagent learning. Mobile robots, such as autonomous underwater vehicles (AUVs), can use predictions of communication performance to anticipate where they are likely to be connected to the communication network. The first challenge is to predict the acoustic communication performance of AUVs from a set of measurements. We compare two methodologies using a simple model of communication performance. Next, we propose a model-based learning methodology for the prediction of underwater acoustic performance using a realistic model. The methodology first estimates the covariance matrix and then predicts the communication performance. The efficiency of the framework is validated with simulations and experimental data from field trials. The second challenge regards the efficient execution of Gaussian processes using multiple agents and communicating as little as possible. We propose decentralized algorithms that facilitate local computations at the expense of inter-agent communications. Moreover, we propose a nearest neighbor selection strategy that enables a subset of agents to participate in the prediction. Illustrative examples with real world data are provided to validate the efficiency of the algorithms.

This thesis presents an evaluation of the performance, in terms of throughput and latency, of two Media Access Control (MAC) mechanisms in Underwater Acoustic Networks (UANs), using a model designed in the COTS simulation tool OPNET 10.5. The carrier sense multiple access with collision avoidance is the predominant approach for implementing the MAC mechanism in UANs. However, the underwater acoustic environment is characterized by extreme propagation delays and limited bandwidth, which suggests that an Aloha-like scheme may merit consideration. The performance of these two schemes was compared with respect to two topologies: tree and grid. The results showed that an Aloha-like scheme that does not segment messages outperforms the contention-based scheme under all load conditions, in terms of both throughput and latency, for the two topologies. This thesis is the first to establish that Aloha-like MAC mechanisms can be more than a limited alternative for lightly loaded networks; more specifically, they can be the preferred choice for an environment with large propagation delays. / Lieutenant Commander, Portuguese Navy

This thesis discusses a new approach to tracking the REMUS 100 AUV using a modified version of the Florida Atlantic University (FAU) ultrashort baseline (USBL) acoustic positioning system (APS). The REMUS 100 is designed to utilize a long baseline (LBL) acoustic positioning system to obtain positioning data in mid-mission. If the placement of one of the transponders of the LBL field is known, then tracking the position of the REMUS 100 AUV using a passive USBL array is possible. As part of the research for this thesis, the FAU USBL system was used to find a relative range between the REMUS 100 ranger and a LBL transponder. This relative range was then combined with direction of arrival information and LBL field component position information to determine an absolute position of the REMUS 100 ranger. The outcome was the demonstration of a passive USBL based tracking system. / by Kyle L. Seaton. / Thesis (M.S.C.S.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Thesis (M.S.)--University of Delaware, 2006. / Principal faculty advisor: Robert P. Gilbert, Dept. of Mathematical Sciences. Includes bibliographical references.

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, and mine reconnaissance. The enabling technology for these applications is acoustic wireless networking. UnderWater Acoustic Sensor Networks (UW-ASNs) consist of sensors and Autonomous Underwater Vehicles (AUVs) deployed to perform collaborative monitoring tasks. The objective of this research is to explore fundamental key aspects of underwater acoustic communications, propose communication architectures for UW-ASNs, and develop efficient sensor communication protocols tailored for the underwater environment. Specifically, different deployment strategies for UW-ASNs are studied, and statistical deployment analysis for different architectures is provided. Moreover, a model characterizing the underwater acoustic channel utilization efficiency is introduced. The model allows setting the optimal packet size for underwater communications. Two distributed routing algorithms are proposed for delay-insensitive and delay-sensitive applications. The proposed routing solutions allow each node to select its next hop, with the objective of minimizing the energy consumption taking the different application requirements into account. In addition, a resilient routing solution to guarantee survivability of the network to node and link failures in long-term monitoring missions is developed. Moreover, a distributed Medium Access Control (MAC) protocol for UW-ASNs is proposed. It is a transmitter-based code division multiple access scheme that incorporates a novel closed-loop distributed algorithm to set the optimal transmit power and code length. It aims at achieving high network throughput, low channel access delay, and low energy consumption. Finally, an efficient cross-layer communication solution tailored for multimedia traffic (i.e., video and audio streams, still images, and scalar sensor data) is introduced.

Underwater Acoustic Sensor Networks (UW-ASNs) have the potential to enable many applications such as environmental monitoring, undersea exploration and distributed tactical surveillance. In order to realize the potential gains of these applications, it is essential that the sensor nodes can be accurately located in a three dimensional underwater sensor network topology. Although many localization protocols have been proposed recently for terrestrial sensor networks, the unique characteristics of the underwater acoustic communication channel, such as high and variable propagation delay, necessitate new localization protocols. In order to address this need, a localization protocol for UW-ASN, Three-Dimensional Underwater Localization (3DUL), is presented in this thesis. 3DUL achieves network-wide robust 3D localization by using a distributed and iterative algorithm. Importantly, 3DUL exploits only three surface buoys for localization. The sensor nodes leverage the low speed of sound to accurately determine the inter-node distances. We show through simulation experiments that the localization accuracy does not degrade significantly with an increase in the number of nodes, making 3DUL scalable.

Sonar is the traditional method of underwater target detection and tracking. However, using traditional sonar arrays may be difficult and impractical in some mission-critical scenarios as they require a ship or a submersible to be mounted on or towed by. Alternatively, Underwater Acoustic Sensor Networks (UW-ASN) offer a promising solution approach. In this thesis, a target tracking algorithm for UW-ASN, Three-Dimensional Underwater Target Tracking (3DUT) is presented. The objective of 3DUT is to collaboratively accomplish accurate tracking of underwater targets with minimum energy expenditure. Based on the time-of-arrival (ToA) of the echoes from the target after transmitting acoustic pulses from the sensors, the ranges of the nodes to the target are determined, and trilateration is used to obtain the location of the target. The location and the calculated velocity of the target are then exploited to achieve tracking. In order to realize energy-effective target tracking, 3DUT incorporates a new target movement-based duty cycle mechanism. To avoid rapid depletion of energy resources of boundary nodes due to continuous surveillance, 3DUT employs an adaptive procedure to find, designate, and activate new boundary nodes. Performance evaluation shows that 3DUT is a promising alternative to the traditional sonar based target tracking approaches especially for on-demand surveillance applications.

In this thesis, localization of the underwater sound sources using matched field processing technique is considered. Localization of the underwater sound sources is one of the most important problems encountered in underwater acoustics and signal processing. Many techniques were developed to localize sources in range, depth and bearing angle. However, most of these techniques do not consider or only slightly takes into account the environmental factors that dramatically effect the propagation of underwater sound. Matched field processing has been developed as a technique that fully considers the environmental factors. Matched field processing has proven to be successful in many applications such as localization of sources in range and depth, the determination of environmental parameters, and the evaluation of model accuracies. In this study, first a comparative analysis of narrowband matched field processors is given. Namely four main processors: Bartlett processor, Minimum Variance Distortionless Response (MVDR) processor, MVDR with neighboring location constraints and MVDR with environmental perturbation constraints are compared in terms of their probability of correct localization under certain environmental conditions. Secondly, a performance assesment for the most common broadband matched field processors is made. The correct localization performances for incoherent broadband matched field processor, Tolstoy/Michalopoulo&#039 / s coherent matched field processor and broadband matched field processor with environmental perturbation constraints is given for certain environmental conditions. Finally, a new weighting approach to combine data for broadband matched field processing is introduced. The fact that information from different frequencies may have different reliability depending on the environmental conditions is considered to develop a weighting scheme. It is shown that a performance gain compared to existing processors can be achieved by using the weighting scheme introduced in this study.