Underwater target tracking by means of acoustic and electromagnetic data fusion

Dalberg, E.; Lauberts, A.; Lennartsson, R.K.; Levonen, M.J.; Persson, Leif

doi:10.1109/icif.2006.301613

Cited by 29 publications

(8 citation statements)

References 2 publications

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“…The measurement model for the acoustic sensor contains a base frequency measurement model (narrow-band processing), an acoustic spectrum pattern model (narrow-band processing), and an acoustic sound pressure measurement model (wide-band processing) [28,29]. In this paper, sensors measure distance to the target via transmitting acoustic pulses and calculate time of arrival (TOA) from the pulse to echoes.…”

Section: Problem Formulationmentioning

confidence: 99%

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Liu

Zhang

et al. 2017

Sensors

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Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

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Section: Problem Formulationmentioning

confidence: 99%

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Liu

Zhang

et al. 2017

Sensors

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“…Dalberg et al . [ 65 ] fused electromagnetic and acoustic data to track surface vessels using underwater sensor nodes. In [ 66 ], Silent Localization Using Magnetometers (SLUM) is proposed.…”

Section: Hybrid Localization Algorithmsmentioning

confidence: 99%

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

Han

Jiang

Shu

et al. 2012

Sensors

186

119

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In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs.

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“…Tracking and estimation were performed using an unscented Kalman filter [13] and an unscented particle filter [14]. Dalberg et al [15] fused electromagnetic and acoustic data to track surface vessels using underwater sensors.…”

Section: Eurasip Journal On Advances In Signal Processingmentioning

confidence: 99%

“…Several studies of the electromagnetic characteristics of the maritime environment have stated that the permeability of the seabed differs considerably from the permeability of air or water. The environment should therefore be modeled as a horizontally stratified model with site specific permeability and layer thickness for each segment [12,15,16]. This has not been included in our simulation study but should be considered in field experiments.…”

Section: Eurasip Journal On Advances In Signal Processingmentioning

confidence: 99%

Silent Localization of Underwater Sensors Using Magnetometers

Callmer

Skoglund

Gustafsson

2010

EURASIP J. Adv. Signal Process.

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Sensor localization is a central problem for sensor networks. If the sensor positions are uncertain, the target tracking ability of the sensor network is reduced. Sensor localization in underwater environments is traditionally addressed using acoustic range measurements involving known anchor or surface nodes. We explore the usage of triaxial magnetometers and a friendly vessel with known magnetic dipole to silently localize the sensors. The ferromagnetic field created by the dipole is measured by the magnetometers and is used to localize the sensors. The trajectory of the vessel and the sensor positions are estimated simultaneously using an Extended Kalman Filter (EKF). Simulations show that the sensors can be accurately positioned using magnetometers.

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Underwater target tracking by means of acoustic and electromagnetic data fusion

Cited by 29 publications

References 2 publications

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

Silent Localization of Underwater Sensors Using Magnetometers

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