Localization of Mobile Nodes in an Underwater Distributed Antenna System

Carroll, Patrick; Domrese, Katherine; Zhou, Hao; Zhou, Shengli; Willett, Peter

doi:10.1145/2671490.2674581

Cited by 9 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… Kalman filter localization (KFL): It is an enhanced localization technique for moving objects in the underwater network. It is a real‐world implementation algorithm that considers the Doppler shift of signal in moving node and estimates the distance between AUV and the nodes that have an antenna and do the two‐way communication for location estimation 36 Three‐dimensional underwater localization (3DUL): The 3DUL algorithm provides the iterative and dynamic solution for underwater node localization accurately.…”

Section: Classification Of Node Localization In Uwsnmentioning

confidence: 99%

Analysis and performance evaluation of computation models for node localization in deep sea using UWSN

Kumar,

Goyal,

Singh

et al. 2024

Int J Communication

View full text Add to dashboard Cite

SummaryUnderwater wireless sensor network (UWSN) connects the real world to the hidden resources available deep into the sea using sensor nodes deployed sparsely and are interconnected to gather information for any movement/change in the ocean. The computed information on nodes obtained from concurrently running UWSN's applications will be meaningful, only if the location of this change will be identified. Nevertheless, it is always difficult to obtain the exact location coordinates of any misadventure like tectonic plate's movement but using localization algorithms in UWSN helps to obtain the coordinates. Since localization algorithms for terrestrial networks are not feasible for UWSN because of environmental challenges. Moreover, GPS systems do not work after 15 m of depth and the radio frequency gets suppressed. So, the requirement arises to analyze existing localization approaches in the deep sea where acoustic signals are used for communication and data transfer. In this paper, along with describing the UWSN's applications and challenges, the underwater localization schemes are reviewed to present, summarize, and mention the scope of improvement. Further, classification into range‐based and range‐free categories of these schemes is depicted with implementation in the NS2.30 simulation environment of some of the recent techniques to showcase the reasons for better performance.

show abstract

Section: Classification Of Node Localization In Uwsnmentioning

confidence: 99%

Analysis and performance evaluation of computation models for node localization in deep sea using UWSN

Kumar,

Goyal,

Singh

et al. 2024

Int J Communication

View full text Add to dashboard Cite

show abstract

“…All nodes should meet to share data at any time, i.e., every individual sensor node can retrieve all readings and execute the process of localization before carrying all data back to the active or reference nodes. Each sensor node in the corresponding destination frame can communicate completely with other nodes and has no accident or interference problems [18]. At time t 0 , the active sensor node emits a single message requesting location through all of the listening nodes and each node gets message at the time t n,n .…”

Section: Procedures and Basics Of Localizationmentioning

confidence: 99%

A Review of Underwater Localization Techniques, Algorithms, and Challenges

et al. 2020

View full text Add to dashboard Cite

Recently, there has been increasing interest in the field of underwater wireless sensor networks (UWSNs), which is a basic source for the exploration of the ocean environment. A range of military and civilian applications is anticipated to assist UWSN. The UWSN is being developed by the extensive wireless sensor network (WSN) applications and wireless technologies. Therefore, in this paper, a review has been presented which unveils the existing challenges in the underwater environment. In this review, firstly, an introduction to UWSN is presented. After that, underwater localizations and the basics are presented. Secondly, the paper focuses on the architecture of UWSN and technologies used for underwater acoustic sensor network (UASN) localization. Various localization techniques are discussed in the paper classified by centralized and distributed localizations. They are further classified into estimated and prediction-based localizations. Also, various underwater localization algorithms are discussed, which are grouped by the algorithms based on range and range-free schemes. Finally, the paper focuses on the challenges existing in underwater localizations, underwater acoustic communications with conclusions.

show abstract

“…In (Xu et al 2015), the concept of coplanarity and quasi-newton algorithm for less positioning error and less bad node proportion was illustrated. The authors proposed the Kalman filter and probabilistic data association filter (Carroll et al 2016) to evaluate the location coordinates of the nodes. This incorporated the Doppler speed calculation for enhancing the communication between nodes.…”

Section: Related Workmentioning

confidence: 99%

Fault-resilient localization using fuzzy logic and NSGA II-based metaheuristic scheme for UWSNs

2021

View full text Add to dashboard Cite

Localization is the fundamental problem for event detecting and monitoring due to the mobility of nodes UWSNs. In the literature, researchers have examined the localization problem through optimization schemes for evaluating the accurate location of unknown target nodes . However, the existing schemes have not considered the failure of anchor nodes during obstacles, natural disasters and environmental interferences. Due to this, the network leads to high localization error and energy depletion. Therefore, in this paper, we considered anchor node failure and bad distance computational between anchor-target pair for better localization. For this, fault-resilient localization using FL and NSGA II-based metaheuristic scheme is proposed for UWSNs. In this scheme, first, we refined the correction value of an anchor node to improve the distance between anchor-target pair. Afterward, FL and NSGA II are applied to identify the set of optimal anchor nodes for the fault-resilient localization process. Furthermore, we have also incorporated fitness value with the three parameters such as residual energy, modified anchor-target distance and a number of the connected nodes as the input parameters, whereas probability is the output for the selection of optimal anchor nodes. Performance evaluation of the proposed scheme outperforms the existing scheme in terms of average localization error, better coverage positioning, localized and bad node proportion with a fast convergence rate under different network scenarios.

show abstract

Localization of Mobile Nodes in an Underwater Distributed Antenna System

Cited by 9 publications

References 8 publications

Analysis and performance evaluation of computation models for node localization in deep sea using UWSN

Analysis and performance evaluation of computation models for node localization in deep sea using UWSN

A Review of Underwater Localization Techniques, Algorithms, and Challenges

Fault-resilient localization using fuzzy logic and NSGA II-based metaheuristic scheme for UWSNs

Contact Info

Product

Resources

About