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

Self-organizing Fast Routing Protocols for Underwater Acoustic Communications Networks

To address this problem, in this thesis we propose a cross-layer proactive routing initialization mechanism that does not require additional measurements and, at the same time, is energy efficient. Two routing protocols are proposed: Self-Organized Fast Routing Protocol for Radial Underwater Networks (SOFRP) for radial topology and Self-organized Proactive Routing Protocol for Non-uniformly Deployed Underwater Networks (SPRINT) for a randomly deployed network. SOFRP is based on the algorithm to recreate a radial topology with a gateway node, such that packets always use the shortest possible path from source to sink, thus minimizing consumed energy. Collisions are avoided as much as possible during the path initialization. The algorithm is suitable for 2D or 3D areas, and automatically adapts to a varying number of nodes. In SPRINT the routing path to the gateway is formed on the basis of the distance, measured by the signal strength received. The data sending node prefers to choose the neighbor node which is closest to it. It is designed to achieve high data throughput and low energy consumption of the nodes. There is a tradeoff between the throughput and the energy consumption: more distance needs more transmission energy, and more relay nodes (hops) to the destination node affects the throughput. Each hop increases the packet delay and decreases the throughput. Hence, energy consumption requires nearest nodes to be chosen as forwarding node whereas the throughput requires farthest node to be selected to minimize the number of hops. Fecha de lectura de Tesis Doctoral: 11 mayo 2020Underwater Wireless Sensor Networks (UWSNs) constitute an emerging technology for marine surveillance, natural disaster alert and environmental monitoring. Unlike terrestrial Wireless Sensor Networks (WSNs), electromagnetic waves cannot propagate more than few meters in water (high absorption rate). However, acoustic waves can travel long distances in underwater. Therefore, acoustic waves are preferred for underwater communications, but they travel very slow compare to EM waves (typical speed in water is 1500 m/s against 2x10^8 m/s for EM waves). This physical effect makes a high propagation delay and cannot be avoided, but the end-to-end packet delay it can be reduced. Routing delay is one of the major factors in end-to-end packet delay. In reactive routing protocols, when a packet arrives to a node, the node takes some time to select the node to which the data packet would be forwarded. We may reduce the routing delay for time-critical applications by using proactive routing protocols. Other two critical issues in UWSNs are determining the position of the nodes and time synchronization. Wireless sensor nodes need to determine the position of the surrounding nodes to select the next node in the path to reach the sink node. A Global Navigation Satellite System (GNSS) cannot be used because of the very short underwater range of the GNSS signal. Timestamping to estimate the distance is possible but the limited mobility of the UWSN nodes and variation in the propagation speed of the acoustic waves make the time synchronization a challenging task. For these reasons, terrestrial WSN protocols cannot be readily used for underwater acoustic networks

Localización y posicionamiento de equipos subacuáticos mediante ultrasonidos

[EN] As part of the project Automatización de la iNspección y el renDimiento Remotos de Explotaciones de Acuicultura marina (ANDREA), an improvement in the navigation of an autonomous underwater vehicle by obtaining distance to an underwater sensor network is proposed. In this work, a literature review in underwater localization and positioning has been realized to obtain a knowledge base and provide a solution for this objective. As a result, a first survey has been attained and a first solution has been developed. This solution is an application that allows the AUV can estimate their distances to a set of beacons in fixed positions in order to enable the AUV calculates its location when needed.[ES] Como parte del proyecto Automatización de la iNspección y el renDimiento Remotos de Explotaciones de Acuicultura marina (ANDREA) se propone mejorar la navegación de un vehículo autónomo subacuático mediante la obtención de distancias a una red inalámbrica de sensores subacuáticos. En este trabajo se ha realizado una búsqueda bibliográfica de técnicas de localización y posicionamiento en el medio subacuático para obtener una base de conocimiento apropiada y aportar una solución viable a este objetivo. Como resultado se ha realizado un primer estado del arte en localización subacuática y se ha desarrollado una primera solución. Esta solución consiste en una aplicación que permite al AUV estimar sus distancias a un conjunto de balizas en posiciones fijas para que pueda calcular su localización cuando sea necesario.Sáez Cañete, R. (2014). Localización y posicionamiento de equipos subacuáticos mediante ultrasonidos. http://hdl.handle.net/10251/59503Archivo delegad

Analysis of relevant technical issues and deficiencies of the existing sensors and related initiatives currently set and working in marine environment. New generation technologies for cost-effective sensors

The last decade has seen significant growth in the field of sensor networks, which are currently collecting large amounts of environmental data. This data needs to be collected, processed, stored and made available for analysis and interpretation in a manner which is meaningful and accessible to end users and stakeholders with a range of requirements, including government agencies, environmental agencies, the research community, industry users and the public. The COMMONSENSE project aims to develop and provide cost-effective, multi-functional innovative sensors to perform reliable in-situ measurements in the marine environment. The sensors will be easily usable across several platforms, and will focus on key parameters including eutrophication, heavy metal contaminants, marine litter (microplastics) and underwater noise descriptors of the MSFD. The aims of Tasks 2.1 and 2.2 which comprise the work of this deliverable are: • To obtain a comprehensive understanding and an up-to-date state of the art of existing sensors. • To provide a working basis on “new generation” technologies in order to develop cost-effective sensors suitable for large-scale production. This deliverable will consist of an analysis of state-of-the-art solutions for the different sensors and data platforms related with COMMONSENSE project. An analysis of relevant technical issues and deficiencies of existing sensors and related initiatives currently set and working in marine environment will be performed. Existing solutions will be studied to determine the main limitations to be considered during novel sensor developments in further WP’s. Objectives & Rationale The objectives of deliverable 2.1 are: • To create a solid and robust basis for finding cheaper and innovative ways of gathering data. This is preparatory for the activities in other WPs: for WP4 (Transversal Sensor development and Sensor Integration), for WP(5-8) (Novel Sensors) to develop cost-effective sensors suitable for large-scale production, reducing costs of data collection (compared to commercially available sensors), increasing data access availability for WP9 (Field testing) when the deployment of new sensors will be drawn and then realized