240 research outputs found
Localization Algorithms of Underwater Wireless Sensor Networks: A Survey
In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodesā mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs
Wireless Sensor Networks for Underwater Localization: A Survey
Autonomous Underwater Vehicles (AUVs) have widely deployed in marine investigation and ocean exploration in recent years. As the fundamental information, their position information is not only for data validity but also for many real-world applications. Therefore, it is critical for the AUV to have the underwater localization capability. This report is mainly devoted to outline the recent advance- ment of Wireless Sensor Networks (WSN) based underwater localization. Several classic architectures designed for Underwater Acoustic Sensor Network (UASN) are brie y introduced. Acoustic propa- gation and channel models are described and several ranging techniques are then explained. Many state-of-the-art underwater localization algorithms are introduced, followed by the outline of some existing underwater localization systems
A Bayesian Approach for Localization of Acoustic Emission Source in Plate-Like Structures
This paper presents a Bayesian approach for localizing acoustic emission (AE) source in plate-like structures with consideration of uncertainties from modeling error and measurement noise. A PZT sensor network is deployed to monitor and acquire AE wave signals released by possible damage. By using continuous wavelet transform (CWT), the time-of-flight (TOF) information of the AE wave signals is extracted and measured. With a theoretical TOF model, a Bayesian parameter identification procedure is developed to obtain the AE source location and the wave velocity at a specific frequency simultaneously and meanwhile quantify their uncertainties. It is based on Bayesā theorem that the posterior distributions of the parameters about the AE source location and the wave velocity are obtained by relating their priors and the likelihood of the measured time difference data. A Markov chain Monte Carlo (MCMC) algorithm is employed to draw samples to approximate the posteriors. Also, a data fusion scheme is performed to fuse results identified at multiple frequencies to increase accuracy and reduce uncertainty of the final localization results. Experimental studies on a stiffened aluminum panel with simulated AE events by pensile lead breaks (PLBs) are conducted to validate the proposed Bayesian AE source localization approach
Advances in Sonar Technology
The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here
Online Audio-Visual Multi-Source Tracking and Separation: A Labeled Random Finite Set Approach
The dissertation proposes an online solution for separating an unknown and time-varying number of moving sources using audio and visual data. The random finite set framework is used for the modeling and fusion of audio and visual data. This enables an online tracking algorithm to estimate the source positions and identities for each time point. With this information, a set of beamformers can be designed to separate each desired source and suppress the interfering sources
Algorithms for propagation-aware underwater ranging and localization
MenciĆ³n Internacional en el tĆtulo de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of
the crucial research problems of modern time. Underwater localization stands among the
key issues on the way to the proper inspection and monitoring of this significant part of our
world. In this thesis, we investigate and tackle different challenges related to underwater
ranging and localization. In particular, we focus on algorithms that consider underwater
acoustic channel properties. This group of algorithms utilizes additional information
about the environment and its impact on acoustic signal propagation, in order to improve
the accuracy of location estimates, or to achieve a reduced complexity, or a reduced
amount of resources (e.g., anchor nodes) compared to traditional algorithms.
First, we tackle the problem of passive range estimation using the differences in the
times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand
energy- effective algorithm that can be used for the localization of autonomous
underwater vehicles (AUVs), and utilizes information about signal propagation. We study
the accuracy of this method in the simplified case of constant sound speed profile (SSP)
and compare it to a more realistic case with various non-constant SSP. We also propose
an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic
propagation via ray models, takes into account the difference between rectilinear and
non-rectilinear sound ray paths. According to our evaluation, this offers improved range
estimation results with respect to standard algorithms that consider the actual value of
the speed of sound.
We then propose an algorithm suitable for the non-invasive tracking of AUVs or
vocalizing marine animals, using only a single receiver. This algorithm evaluates the
underwater acoustic channel impulse response differences induced by a diverse sea
bottom profile, and proposes a computationally- and energy-efficient solution for passive
localization.
Finally, we propose another algorithm to solve the issue of 3D acoustic localization
and tracking of marine fauna. To reach the expected degree of accuracy, more sensors
are often required than are available in typical commercial off-the-shelf (COTS) phased
arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple
COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of
state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We
propose a solution for passive 3D localization and tracking using a wideband acoustic
array of arbitrary shape, and validate the algorithm in multiple experiments, involving
both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under
project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en IngenierĆa TelemĆ”tica por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio FernĆ”ndez Anta.- Vocal: Santiago Zazo Bell
Localization, Mapping and SLAM in Marine and Underwater Environments
The use of robots in marine and underwater applications is growing rapidly. These applications share the common requirement of modeling the environment and estimating the robotsā pose. Although there are several mapping, SLAM, target detection and localization methods, marine and underwater environments have several challenging characteristics, such as poor visibility, water currents, communication issues, sonar inaccuracies or unstructured environments, that have to be considered. The purpose of this Special Issue is to present the current research trends in the topics of underwater localization, mapping, SLAM, and target detection and localization. To this end, we have collected seven articles from leading researchers in the field, and present the different approaches and methods currently being investigated to improve the performance of underwater robots
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