Multi-stage AUV-aided Localization for Underwater Wireless Sensor Networks

Waldmeyer, Marc; Tan, Hwee-Pink; Seah, Winston K.G.

doi:10.1109/waina.2011.90

Cited by 57 publications

(45 citation statements)

References 8 publications

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“…The authors in [53] have used AUV to assist in localization underwater. The designed system is acoustics based and uses acoustic localization techniques.…”

Section: Assisted Navigationmentioning

confidence: 99%

Underwater Sensor Network Applications: A Comprehensive Survey

Felemban

Shaikh

Qureshi

et al. 2015

International Journal of Distributed Sensor Networks

329

190

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There is no escaping fact that a huge amount of unexploited resources lies underwater which covers almost 70% of the Earth. Yet, the aquatic world has mainly been unaffected by the recent advances in the area of wireless sensor networks (WSNs) and their pervasive penetration in modern day research and industrial development. The current pace of research in the area of underwater sensor networks (UWSNs) is slow due to the difficulties arising in transferring the state-of-the-art WSNs to their underwater equivalent. Maximum underwater deployments rely on acoustics for enabling communication combined with special sensors having the capacity to take on harsh environment of the oceans. However, sensing and subsequent transmission tend to vary as per different subsea environments; for example, deep sea exploration requires altogether a different approach for communication as compared to shallow water communication. This paper particularly focuses on comprehensively gathering most recent developments in UWSN applications and their deployments. We have classified the underwater applications into five main classes, namely, monitoring, disaster, military, navigation, and sports, to cover the large spectrum of UWSN. The applications are further divided into relevant subclasses. We have also shown the challenges and opportunities faced by recent deployments of UWSN.

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“…The authors in [53] have used AUV to assist in localization underwater. The designed system is acoustics based and uses acoustic localization techniques.…”

Section: Assisted Navigationmentioning

confidence: 99%

Underwater Sensor Network Applications: A Comprehensive Survey

Felemban

Shaikh

Qureshi

et al. 2015

International Journal of Distributed Sensor Networks

329

190

View full text Add to dashboard Cite

show abstract

“…According to the computation algorithm to be implemented, we classify the computation algorithms into two categories as centralized techniques [15] and distributed methods [16]. The centralized technology performs the localization algorithm at the command center or sink node.…”

Section: Related Workmentioning

confidence: 99%

“…However, the range-free scheme can only get a rough location with little accuracy. The positioning method of [22] is a range-based approach, and is called the multi-stage AUV-assisted positioning scheme that is an improvement of the "multi-stage DNR" scheme. In [22], the DNR is replaced by AUV.…”

Section: Related Workmentioning

confidence: 99%

“…The positioning method of [22] is a range-based approach, and is called the multi-stage AUV-assisted positioning scheme that is an improvement of the "multi-stage DNR" scheme. In [22], the DNR is replaced by AUV. The AUV with known coordinates dives to a pre-programmed depth and begins to traverse the sensor network after the preprogrammed path.…”

Section: Related Workmentioning

confidence: 99%

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Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

Luo

Fan

2017

Preprint

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Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

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“…Nevertheless, the acoustic channel is characterized by its limited bandwidth, high bit error rate, path loss, motion-induced Doppler shift, and so on. 5 (3) Underwater sensor nodes are liable to move or be damaged 6,7 due to the water current caused by external forces such as earthquake, tide, wind velocity, underwater creature touch, or strong electromagnetic interference, which will lead to a dynamic network topology. 8 All above unique characteristics are possible to result in the damage or inaccurate localization of beacon nodes.…”

Section: Introductionmentioning

confidence: 99%

A clustering approach for error beacon filtering in underwater wireless sensor networks

Liu

Guo

2016

International Journal of Distributed Sensor Networks

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Underwater wireless sensor networks are the enabling technology for the aquatic environmental monitoring and exploring and have attracted much attention recently. Due to the highly hostile and unpredictable underwater environments, some beacon nodes tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this article proposes an error beacon filtering algorithm based on K-means clustering. First, the coordinate of each beacon is calculated through an improved trilateration method, and then the beacon with the maximum positioning error is filtered out via the K-means clustering algorithm. The remaining beacons repeat the above processes until the distance error of each beacon does not exceed a preset threshold. The analysis of simulation results indicates that the error beacons can be accurately found and filter out through our proposed error beacon filtering algorithm (based on K-means clustering), and thus the localization accuracy is enhanced. Besides, error beacon filtering algorithm also has a provable low complexity.

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Multi-stage AUV-aided Localization for Underwater Wireless Sensor Networks

Cited by 57 publications

References 8 publications

Underwater Sensor Network Applications: A Comprehensive Survey

Underwater Sensor Network Applications: A Comprehensive Survey

Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

A clustering approach for error beacon filtering in underwater wireless sensor networks

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