Underwater localization using SAR satellite data.

This study delves into the realm of Underwater Wireless Sensor Networks (UWSN) and explores contemporary methods of ocean exploration. It provides an extensive background on UWSN, detailing existing approaches to underwater localization. The study then introduces a novel contribution to this domain by leveraging advanced satellite technology. Employing a pre-trained deep learning model from ArcGIS, static ships within the study area are identified using C-band Synthetic Aperture Radar (SAR) satellite imagery. The identified ship locations serve as reference nodes for underwater localization. Utilizing range-based multilateration in the UnetStack environment, the study achieves precise localization of underwater nodes. The proposed approach demonstrates an error of less than 1% when compared to the actual positions of the underwater nodes, showcasing its effectiveness in enhancing the field of underwater exploration and localization

Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms.

Localization in large-scale underwater swarm robotic systems has increasingly attracted research and industry communities’ attention. An optimized confidence-based localization algorithm is proposed for improving localization coverage and accuracy by promoting robots with high confidence of location estimates to references for their neighboring robots. Confidence update rules based on Bayes filters are proposed based on localization methods’ error characteristics where expected localization error is generated based on measurements such as operational depth and traveled distance. Parameters of the proposed algorithm are then optimized using the Evolutionary Multi-objective Optimization algorithm NSGA-II for localization error and trilateration utilization minimization while maximizing localization confidence and Ultra-Short Base Line utilization. Simulation studies show that a wide localization coverage can be achieved using a single Ultra-Short Base Line system and localization mean error can be reduced by over 45% when algorithm’s parameters are optimized in an underwater swarm of 100 robots

Relay selection in mobile multihop relay network

Mobile Multihop Relay (MMR) network is an attractive and low-cost solution for expanding service coverage and enhancing throughput of the conventional single hop network. However, mobility of Mobile Station (MS) in MMR network might lead to performance degradation in terms of Quality of Service (QoS). Selecting an appropriate Relay Station (RS) that can support data transmission for high mobility MS to enhance QoS is one of the challenges in MMR network. The main goal of the work is to develop and enhance relay selection mechanisms that can assure continuous connectivity while ensuring QoS in MMR network using NCTUns simulation tools. The approach is to develop and enhance relay selection that allows cooperative data transmission in transparent relay that guarantees continuous connectivity. The proposed relay selection defined as Co-ReSL depends on weightage of SNR, α and weightage of Link Expiration Time (LET), β. The QoS performances of the proposed relay selections are in terms of throughput and average end-to-end (ETE) delay. The findings for Co-ReSL shows that at heavy traffic load, throughput increases up to 5.7% and average ETE delay reduces by 7.5% compared to Movement Aware Greedy Forwarding (MAGF) due to cooperative data transmission in selective links. The proposed relay selection mechanisms can be applied in any high mobility multi-tier cellular network

Transmission Scheduling Technique for A Propagation transfer using Sensing Protocol Under water Acoustic Wireless Sensor Networks.

 As detector nodes square measure typically powered devices, the vital aspects to face concern the way to cut back the energy consumption of nodes, so the network lifespan may be extended to cheap times. Mobile underwater networks with acoustic communications square measure faced with many distinctive challenges like high transmission power utilization, giant propagation delay and node quality. In which Protocol multichip wireless network that uses multiple channel and dynamic channel choice technique. The comparison is conceded out by means that of analytical models, that square measure wont to confine the activities of a node that acts in line with either thought-about specifically for the underwater acoustic surroundings. The delay-aware opportunist transmission planning rule has been principally designed for underwater mobile detector networks. It uses passively obtained native info to reinforce the probabilities of synchronic transmissions whereas reducing collisions. Together with that, a straightforward performance mechanism that allows multiple outstanding packets at the sender facet, facultative multiple transmission sessions has been projected, that successively considerably improves the turnout. Every node learns neighboring node’s propagation delay info and their expected transmission schedules by passively overhearing packet transmissions through the institution of the new developed Macintosh protocol referred to as DOTS. This protocol principally aspires to attain higher channel utilization by harnessing each temporal and spatial recycle. The simulation results exemplify that DOTS provides truthful, medium access even with node quality. Thence this protocol additionally saves transmission energy by avoiding collisions whereas increasing turnout. It additionally achieves a turnout many times over that of the Slotted FAMA, whereas providing connected savings in energy. understanding that protocol is additional suited to given network setting and square measure expected to be of facilitate in planning novel protocol that presumably surmount presently out there solutions. Node monitor native underwater activities and report collected detector knowledge exploitation acoustic multi-hop routing to alternative mobile nodes for collaboration or just to a far off knowledge assortment center

Confidence-based Underwater Localization Scheme for Large-Scale Mobile Sensor Networks

The absence of Global Positioning System in underwater environment predominates in the challenges of underwater vehicles navigation or sensor nodes tracking. Localization of single or few underwater vehicles has been fostered in recent years. However, online simultaneous tracking of large-scale mobile sensor network is still a very challenging research area due to the high cost and the very limited number of vehicles that can be simultaneously localized using Ultra-Short Base Line (USBL) system. We propose a confidence-based localization algorithm for large-scale underwater mobile sensor networks that employs high precision localized sensor nodes in neighboring sensor nodes localization. Numerical simulation shows that a swarm of 100 sensor nodes can be tracked using a single USBL system, range measurement sensors and communication modems

A survey on uninhabited underwater vehicles (UUV)

ASME Early Career Technical Conference, ASME ECTC, October 2-3, 2009, Tuscaloosa, Alabama, USAThis work presents the initiation of our underwater robotics research which will be focused on underwater vehicle-manipulator systems. Our aim is to build an underwater vehicle with a robotic manipulator which has a robust system and also can compensate itself under the influence of the hydrodynamic effects. In this paper, overview of the existing underwater vehicle systems, thruster designs, their dynamic models and control architectures are given. The purpose and results of the existing methods in underwater robotics are investigated

Anomaly Detection in UASN Localization Based on Time Series Analysis and Fuzzy Logic

[EN] Underwater acoustic sensor network (UASN) offers a promising solution for exploring underwater resources remotely. For getting a better understanding of sensed data, accurate localization is essential. As the UASN acoustic channel is open and the environment is hostile, the risk of malicious activities is very high, particularly in time-critical military applications. Since the location estimation with false data ends up in wrong positioning, it is necessary to identify and ignore such data to ensure data integrity. Therefore, in this paper, we propose a novel anomaly detection system for UASN localization. To minimize computational power and storage, we designed separate anomaly detection schemes for sensor nodes and anchor nodes. We propose an auto-regressive prediction-based scheme for detecting anomalies at sensor nodes. For anchor nodes, a fuzzy inference system is designed to identify the presence of anomalous behavior. The detection schemes are implemented at every node for enabling identification of multiple and duplicate anomalies at its origin. We simulated the network, modeled anomalies and analyzed the performance of detection schemes at anchor nodes and sensor nodes. The results indicate that anomaly detection systems offer an acceptable accuracy with high true positive rate and F-Score.Das, AP.; Thampi, SM.; Lloret, J. (2020). Anomaly Detection in UASN Localization Based on Time Series Analysis and Fuzzy Logic. Mobile Networks and Applications (Online). 25(1):55-67. https://doi.org/10.1007/s11036-018-1192-y556725