Underwater Localization Techniques

2021 ◽  
pp. 45-66
Author(s):  
Manisha Bharti ◽  
Poonam Rani Verma
Keyword(s):  
Water Environment ◽  
Underwater Acoustic Communication ◽  
Hybrid Technique ◽  
Sink Node ◽  
Sound Waves ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Mobile Localization ◽  
Unknown Node ◽  
Underwater Localization

Underwater acoustic communication uses sound waves to trans-receive information, diving deep inside water, environment scanning, undersea explorations, disaster prevention, etc. In this chapter, an attempt has been made to cover stationary and mobile localization algorithm. They are further subdivided into distributed and centralized. Each one is further subcategorized into estimation-based and prediction-based schemes. The category therefore extends on the basis of ranging method, communication, and synchronization, some of which are area localization, sensor-based localization, forming a sensor array, motion-aware self-localization, silent localization. Each one will be discussed in detail in this chapter. At last, hybrid technique is also discussed, which combines stationary and mobile techniques. The discussion includes various nodes including anchor node, unknown node, sink node, and reference node. Various methods to follow the techniques are also discussed, which include anchor-based method, ranging method, and message communication.

scholarly journals Localization Algorithm Based on Iterative Centroid Estimation for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Jiang ◽  
Xin Wang ◽  
Li Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Centroid Estimation ◽  
Anchor Nodes ◽  
Localization Precision ◽  
Unknown Node ◽  
Received Signal Strength Indication

According to the application of range-free localization technology for wireless sensor networks (WSNs), an improved localization algorithm based on iterative centroid estimation is proposed in this paper. With this methodology, the centroid coordinate of the space enclosed by connected anchor nodes and the received signal strength indication (RSSI) between the unknown node and the centroid are calculated. Then, the centroid is used as a virtual anchor node. It is proven that there is at least one connected anchor node whose distance from the unknown node must be farther than the virtual anchor node. Hence, in order to reduce the space enclosed by connected anchor nodes and improve the location precision, the anchor node with the weakest RSSI is replaced by this virtual anchor node. By applying this procedure repeatedly, the localization algorithm can achieve a good accuracy. Observing from the simulation results, the proposed algorithm has strong robustness and can achieve an ideal performance of localization precision and coverage.

scholarly journals Improvement of Localization Algorithm for Wireless Sensor Networks Based on DV-Hop

2019 ◽  
Vol 15 (06) ◽  
pp. 53 ◽  
Author(s):  
Xin Qiao ◽  
Fei Chang ◽  
Jing Ling
Keyword(s):  
Estimation Method ◽  
Likelihood Estimation ◽  
Mean Value ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Jump Distance ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Positioning Algorithm

In order to solve the problem that the DV-Hop localization algorithm has large errors in the wireless sensor network environment, this paper uses the minimum mean square criterion to determine the average hop distance of anchor nodes, and then calculates the mean value of the original average hop distance, which ensures that the improved average hop distance is closer to the real average hop distance of the whole network. The estimated distances between nodes are calculated by using the correction value corresponding to the average jump distance of the anchor node; in the positioning stage, when the anchor node is small, the estimated coordinates of unknown nodes are obtained by the minimum-maximum method; when the number of anchor nodes is large, the coordinates of unknown nodes are calculated by the maximum likelihood estimation method; this not only reduces the amount of calculation, but also the accuracy is more stable. This step is not only suitable for DV-Hop algorithm, but also can be used to estimate the coordinates when the distance between the unknown node and the anchor node is known. However, this improved method is only applicable to the premise that the simulation area is not large, so this improvement has its scope of adaptation, according to the needs of choice. Finally, the unknown node coordinates are iteratively optimized by using the quasi Newton method. Simulation results show that the proposed positioning algorithm has higher accuracy and better stability.

Towards multi-scale modelling of complex liquids using hybrid particle—continuum schemes

2008 ◽  
Vol 222 (5) ◽  
pp. 769-776 ◽  
Author(s):  
R Delgado-Buscalioni ◽  
P V Coveney ◽  
G De Fabritiis
Keyword(s):  
Landau Theory ◽  
Coarse Graining ◽  
Longitudinal Momentum ◽  
Hybrid Technique ◽  
Sound Waves ◽  
Multi Scale ◽  
Complex Liquids ◽  
Transversal Shear ◽  
Scale Modelling ◽  
Molecular Nature

Owing to the interplay between molecular and mesoscopic processes, the modelling and simulation of complex liquids at nano- and micron-scales require a multi-scale approach. A hybrid technique is proposed to handle multi-scale phenomena, which retains the full molecular nature of the system where it is of interest while coarse-graining it elsewhere. The method couples molecular dynamics (MD) and fluctuating hydrodynamics (FH) based on the Landau theory. Mean flows involving transport of transversal (shear) and longitudinal momentum (sound) are coupled across the interface of both MD and FH domains. Hydrodynamic fluctuations of mass and momentum are transferred, preserving consistency with hydrodynamics and thermodynamics. Here the hybrid method is illustrated by studying the reflection of water sound waves against a lipid (dimyristoylphosphatidylcholine) monolayer.

Sequence Localization Algorithm Based on 3D Voronoi Diagram in Wireless Sensor Network

2014 ◽  
Vol 644-650 ◽  
pp. 4422-4426 ◽  
Author(s):  
Xi Yang ◽  
Jun Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Voronoi Diagram ◽  
Wireless Sensor ◽  
Weighted Estimate ◽  
Localization Algorithm ◽  
Simulation Experiments ◽  
Localization Accuracy ◽  
3D Space ◽  
Unknown Node

For nodes’ self-localization in wireless sensor networks (WSN), a new localization algorithm called Sequence Localization algorithm based on 3D Voronoi diagram (SL3V) is proposed, which uses 3D Voronoi diagram to divide the localization space.It uses the polyhedron vertices as the virtual beacon nodes and constructs the rank sequence table of virtual beacon nodes. Then it computes Kendall coefficients of the ranks in the optimal rank sequence table and that of the unknown node. Finally, it realizes the weighted estimate of the unknown node by normalization processing Kendall coefficients. Simulation experiments prove that itcan obviously improve the localization accuracy compared with the traditional 2D sequence-based localization and can satisfy the need of localization for 3D space.

scholarly journals An RSSI-based Wireless Sensor Network Localization Algorithm with Error Checking and Correction

2017 ◽  
Vol 13 (12) ◽  
pp. 52 ◽  
Author(s):  
Bo Guan ◽  
Xin Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Anchor Node ◽  
Network Localization ◽  
Error Checking

<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper studies the wireless sensor network localization algorithm based on the received signal strength indicator (RSSI) in detail. Considering the large errors in ranging and localization of nodes made by the algorithm, this paper corrects and compensates the errors of the algorithm to improve the coordinate accuracy of the node. The improved node localization algorithm performs error checking and correction on the anchor node and the node to be measured, respectively so as to make the received signal strength value of the node to be measured closer to the real value. It corrects the weighting factor by using the measured distance between communication nodes to make the coordinate of the node to be measured more accurate. Then, it calculates the mean deviation of localization based on the anchor node close to the node to be measured and compensates the coordinate error. Through the simulation experiment, it is found that the new localization algorithm with error checking and correction proposed in this paper improves the localization accuracy by 5%-6% compared with the weighted centroid algorithm based on RSSI.</span></p>

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

The Research on the Tracking and Positioning Platform Based on the Android Smartphone

2014 ◽  
Vol 631-632 ◽  
pp. 618-622
Author(s):  
Mei Hui Xu ◽  
Ya Qi Wang ◽  
Long Xi Xu
Keyword(s):  
Mobile Phone ◽  
Market Share ◽  
Location Information ◽  
Localization Algorithm ◽  
Important Data ◽  
Security Issues ◽  
Phone Number ◽  
Mobile Localization ◽  
First Time ◽  
The Web

The 3G era, the smartphone market share is higher and higher. The mobile phone based on the Android platform accounts for more than half of the market share. Once the user lost the phone, it is not only hard to find, but also to face important data leak and privacy security issues. So, the demand to provide mobile phone found function appears increasingly urgent. If the mobile phone is lost, this platform can get information on replaced mobile phone SIM card to boot for the first time, and upload the new mobile phone number and current phone location information to the server. It provides users with inquiry function on the web in order to achieve the purpose of tracking the lost mobile phone. The application prospect of this study is widespread, not only limited to track the missing phone, also involves other position service in the life need. The relevant mobile localization algorithm is detailed in this paper.

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