Underwater Localization System Based onVisible-Light Communications Using Neural Networks

2021 ◽  
Author(s):  
Alzahraa Ghonim ◽  
wessam salama ◽  
ABD EL-RAHMAN EL-FIKKY ◽  
Ashraf Khalaf ◽  
Hossam Shalaby
Keyword(s):  
Neural Networks ◽  
Localization System ◽  
Underwater Localization

Towards a Smart Fault Tolerant Indoor Localization System Through Recurrent Neural Networks

2019 ◽  
Author(s):  
Eduardo C. Carvalho ◽  
Bruno V. Ferreira ◽  
Geraldo P. R. Filho ◽  
Pedro H. Gomes ◽  
Gustavo M. Freitas ◽  
...  
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Indoor Localization ◽  
Fault Tolerant ◽  
Localization System

Modified Short Baseline Acoustic Relative Localization System

2013 ◽  
Vol 655-657 ◽  
pp. 882-885
Author(s):  
Cong Ren Lin ◽  
Sheng De Huang ◽  
Fei Yuan
Keyword(s):  
Statistical Error ◽  
Underwater Communication ◽  
Short Baseline ◽  
Localization System ◽  
Acoustic Localization ◽  
Relative Localization ◽  
Underwater Target ◽  
Hyperbolic Positioning ◽  
Underwater Localization ◽  
Positioning Algorithm

Underwater localization is a key element in most underwater communication applications. Since GPS signals highly attenuate in water, precise ranging based techniques for localization need to be developed. In this paper we describe a modified Short Baseline (SBL) acoustic localization system, in which a scheme of multi-channel data acquisition based on LabVIEW, the Generalized Cross Correlation (GCC) algorithm, and the hyperbolic positioning algorithm are used. Simulation results show that the modified SBL acoustic localization system that we proposed can adapt to the underwater harsh environment better, and also can reduce the position statistical error of underwater target significantly.

scholarly journals Device-Free Wireless Localization Using Artificial Neural Networks in Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yongliang Sun ◽  
Xuzhao Zhang ◽  
Xiaocheng Wang ◽  
Xinggan Zhang
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Nonlinear Function ◽  
Ann Model ◽  
Wireless Localization ◽  
Localization System ◽  
Difference Matrices ◽  
Artificial Neural ◽  
Device Free ◽  
Monitoring Area

Currently, localization has been one of the research hot spots in Wireless Sensors Networks (WSNs). However, most localization methods focus on the device-based localization, which locates targets with terminal devices. This is not suitable for the application scenarios like the elder monitoring, life detection, and so on. In this paper, we propose a device-free wireless localization system using Artificial Neural Networks (ANNs). The system consists of two phases. In the off-line training phase, Received Signal Strength (RSS) difference matrices between the RSS matrices collected when the monitoring area is vacant and with a professional in the area are calculated. Some RSS difference values in the RSS difference matrices are selected. The RSS difference values and corresponding matrix indices are taken as the inputs of an ANN model and the known location coordinates are its outputs. Then a nonlinear function between the inputs and outputs can be approximated through training the ANN model. In the on-line localization phase, when a target is in the monitoring area, the RSS difference values and their matrix indices can be obtained and input into the trained ANN model, and then the localization coordinates can be computed. We verify the proposed device-free localization system with a WSN platform. The experimental results show that our proposed device-free wireless localization system is able to achieve a comparable localization performance without any terminal device.

scholarly journals Accurate Localization in Acoustic Underwater Localization Systems

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 762
Author(s):  
Gianni Cario ◽  
Alessandro Casavola ◽  
Gianfranco Gagliardi ◽  
Marco Lupia ◽  
Umberto Severino
Keyword(s):  
Statistical Analysis ◽  
Measurement Unit ◽  
Design Parameters ◽  
Final Position ◽  
Localization System ◽  
Sources Of Error ◽  
Accurate Localization ◽  
Hardware System ◽  
Underwater Localization ◽  
Localization Systems

In underwater localization systems several sources of error may impact in different ways the accuracy of the final position estimates. Through simulations and statistical analysis it is possible to identify and characterize such sources of error and their relative importance. This is especially of use when an accurate localization system has to be designed within required accuracy prescriptions. This approach allows one to also investigate how much these sources of error influence the final position estimates achieved by an Extended Kalman Filter (EKF). This paper presents the results of experiments designed in a virtual environment used to simulate real acoustic underwater localization systems. The paper intends to analyze the main parameters that significantly influence the position estimates achieved by a Short Baseline (SBL) system. Specifically, the results of this analysis are presented for a proprietary localization system constituted by a surface platform equipped with four acoustic transducers used for the localization of an underwater target. The simulator here presented has the purpose of simulating the hardware system and modifying some of its design parameters, such as the base-line length and the errors on the GPS and Inertial Measurement Unit (IMU) units, in order to understand which parameters have to modify for improving the accuracy of the entire positioning system. It is shown that statistical analysis techniques can be of help in determining the best values of these parameters that permit to improve the performance of a real hardware system.

scholarly journals Underwater Localization System Combining iUSBL with Dynamic SBL in ¡VAMOS! Trials

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4710 ◽  
Author(s):  
José Almeida ◽  
Bruno Matias ◽  
António Ferreira ◽  
Carlos Almeida ◽  
Alfredo Martins ◽  
...  
Keyword(s):  
Mining Operation ◽  
Field Trials ◽  
Open Pit ◽  
Localization Problem ◽  
Short Baseline ◽  
Open Pit Mines ◽  
Localization System ◽  
Underwater Mining ◽  
Inland Water Bodies ◽  
Underwater Localization

Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional challenges to the localization problem. This paper presents a novel underwater localization solution, implemented for the ¡VAMOS! project, based on the combination of raw measurements from a short baseline (SBL) array and an inverted ultrashort baseline (iUSBL). An extended Kalman filter (EKF), fusing IMU raw measurements, pressure observations, SBL ranges, and USBL directional angles, estimates the localization of an underwater mining vehicle in 6DOF. Sensor bias and the speed of sound in the water are estimated indirectly by the filter. Moreover, in order to discard acoustic outliers, due to multipath reflections in such a confined and cluttered space, a data association layer and a dynamic SBL master selection heuristic were implemented. To demonstrate the advantage of this new technique, results obtained in the field, during the ¡VAMOS! underwater mining field trials, are presented and discussed.

Low-Cost Underwater Localization System

2020 ◽  
Author(s):  
B. Gerondeau ◽  
L. Galeota ◽  
A. Caudwell ◽  
R. Gouge ◽  
A. Martin ◽  
...  
Keyword(s):  
Low Cost ◽  
Localization System ◽  
Underwater Localization
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