Real-time localization for underwater equipment using an extremely low frequency electric field

Zhang, Jiawei; Yu, Peng; Jiang, Runxiang; Xie, Tao-tao

doi:10.1016/j.dt.2022.06.014

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…Prior research has demonstrated that underwater vehicles' static electric field originates from corrosion and anti-corrosion currents, possessing a significant amount of energy that poses challenges in achieving complete control or elimination. The scalar potential generated several kilometers away can still attain magnitudes reaching tens of nanovolts, thereby providing the potential for utilizing remote electric fields to achieve the detection of underwater vehicles [4]. Given that the far-field source of the underwater vehicle's electrostatic field can be considered to be a constant current element [5], the task of locating an underwater vehicle's electric field over long distances in shallow seas can be reduced to the problem of passively locating a constant current element within a stratified marine environment.…”

Section: Introductionmentioning

confidence: 99%

“…When the horizontal distance between the field source and the field point is 500 m, κ is approximately 3.5%; when the horizontal distance is 1000 m, κ is approximately 18%; when the horizontal distance is 8 km, κ reaches 87%; and when the horizontal distance is 13 km, κ is approximately 91%. 4 ⃝ When other conditions remain unchanged, the smaller d is, the greater κ is. At a depth of d = 500 m, κ is approximately 81% at the plane (1600, 2100) m; at a depth of d = 250 m, κ increases to over 90% at the same position.…”

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confidence: 99%

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An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

Zhang,

Chen,

Sun

et al. 2024

Mathematics

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In order to fulfill the practical application demands of precisely localizing underwater vehicles using passive electric field localization technology, we propose a scalar-potential-based method for the passive electric field localization of underwater vehicles. This method is grounded on an intelligent differential evolution algorithm and is particularly suited for use in three-layer and stratified oceanic environments. Firstly, based on the potential distribution law of constant current elements in a three-layer parallel stratified ocean environment, the mathematical positioning model is established using the mirror method. Secondly, the differential evolution (DE) algorithm is enhanced with a parameter-adaptive strategy and a boundary mutation processing mechanism to optimize the key objective function in the positioning problem. Additionally, the simulation experiments of the current element in the layered model prove the effectiveness of the proposed positioning method and show that it has no special requirements for the sensor measurement array, but the large range and moderate number of sensors are beneficial to improve the positioning effect. Finally, the laboratory experiments on the positioning method proposed in this paper, involving underwater simulated current elements and underwater vehicle tracks, were carried out successfully. The results indicate that the positioning method proposed in this paper can achieve the performance requirements of independent initial value, strong anti-noise capabilities, rapid positioning speed, easy implementation, and suitability in shallow sea environments. These findings suggest a promising practical application potential for the proposed method.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

Zhang,

Chen,

Sun

et al. 2024

Mathematics

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“…Other studies are based on either computer simulations or downscaled laboratory experiments [ 11 , 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…Although quite promising, the results are only based on simulations. Zhang et al recently conducted real-world experiments (1.5 m depth in a water tank and 9 m depth in a shallow sea) [ 15 ]. An electric field induced by a standard current source is used for real-time underwater equipment location.…”

Section: Introductionmentioning

confidence: 99%

In Situ Underwater Localization of Magnetic Sensors Using Natural Computing Algorithms

Alimi¹,

Fisher

Nahir³

2023

Sensors

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In the shallow water regime, several positioning methods for locating underwater magnetometers have been investigated. These studies are based on either computer simulations or downscaled laboratory experiments. The magnetic fields created at the sensors’ locations define an inverse problem in which the sensors’ precise coordinates are the unknown variables. This work addresses the issue through (1) a full-scale experimental setup that provides a thorough scientific perspective as well as real-world system validation and (2) a passive ferromagnetic source with (3) an unknown magnetic vector. The latter increases the numeric solution’s complexity. Eight magnetometers are arranged according to a 2.5 × 2.5 m grid. Six meters above, a ferromagnetic object moves according to a well-defined path and velocity. The magnetic field recorded by the network is then analyzed by two natural computing algorithms: the genetic algorithm (GA) and particle swarm optimizer (PSO). Single- and multi-objective versions are run and compared. All the methods performed very well and were able to determine the location of the sensors within a relative error of 1 to 3%. The absolute error lies between 20 and 35 cm for the close and far sensors, respectively. The multi-objective versions performed better.

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“…It is generally assumed that supercavitating torpedoes (SCT) can only be designed for straight running, which may miss the target at the terminal phase. Te latest researches indicate that a new kind of guidance based on the underwater electric feld of target warships [1,2] can be adopted to enhance SCT combat capability. By measuring the three components of the electric feld, an SCT can obtain the target's location, velocity, and heading angle with a detection range of more than 1 km.…”

Section: Introductionmentioning

confidence: 99%

Composite Terminal Guidance Law for Supercavitating Torpedoes with Impact Angle Constraints

Zhāng

Wang

et al. 2022

Mathematical Problems in Engineering

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A novel composite terminal guidance law with impact angle constraints is proposed for supercavitating torpedoes to intercept maneuvering warships. Based on an adaptive super-twisting algorithm and nonsingular terminal sliding mode (NTSM), the proposed guidance law can guarantee the finite-time convergence of line-of-sight (LOS) angle error and the LOS angular rate error. The new guidance law is a combination of finite-time stability theory, sliding mode control (SMC), tracking differentiator (TD), disturbance observer (DO), and dynamic surface control. A high-order sliding mode TD is used for denoising, tracking, and differentiating the measured target heading angle. A novel DO, with its finite-time stability proved, is designed to estimate the target lateral acceleration for feedforward compensation to attenuate chattering in control input. In the case of a first-order-lag autopilot, a new kind of tracking differentiator is adopted to compute the first-order time derivative of the virtual control command, which can improve the accuracy of dynamic surface control and avoid the “explosion of items” problem encountered with the backstepping control. Finally, numerical simulation results are presented to validate the effectiveness and superiority of the proposed TD, DO, and the composite guidance law.

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Real-time localization for underwater equipment using an extremely low frequency electric field

Cited by 7 publications

References 11 publications

An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

In Situ Underwater Localization of Magnetic Sensors Using Natural Computing Algorithms

Composite Terminal Guidance Law for Supercavitating Torpedoes with Impact Angle Constraints

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