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Ranging in an underwater medium with multiple isogradient sound speed profile layers.

Ramezani H, Leus G - Sensors (Basel) (2012)

Bottom Line: In this paper, we analyze the problem of acoustic ranging between sensor nodes in an underwater environment.The underwater medium is assumed to be composed of multiple isogradient sound speed profile (SSP) layers where in each layer the sound speed is linearly related to the depth.Furthermore, each sensor node is able to measure its depth and can exchange this information with other nodes.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, The Netherlands. h.mashhadiramezani@tudelft.nl

ABSTRACT
In this paper, we analyze the problem of acoustic ranging between sensor nodes in an underwater environment. The underwater medium is assumed to be composed of multiple isogradient sound speed profile (SSP) layers where in each layer the sound speed is linearly related to the depth. Furthermore, each sensor node is able to measure its depth and can exchange this information with other nodes. Under these assumptions, we first show how the problem of underwater localization can be converted to the traditional range-based terrestrial localization problem when the depth information of the nodes is known a priori. Second, we relate the pair-wise time of flight (ToF) measurements between the nodes to their positions. Next, based on this relation, we propose a novel ranging algorithm for an underwater medium. The proposed ranging algorithm considers reflections from the seabed and sea surface. We will show that even without any reflections, the transmitted signal may travel through more than one path between two given nodes. The proposed algorithm analyzes them and selects the fastest one (first arrival path) based on the measured ToF and the nodes' depth measurements. Finally, in order to evaluate the performance of the proposed algorithm we run several simulations and compare the results with other existing algorithms.

No MeSH data available.


Related in: MedlinePlus

Performance of the proposed algorithm for deep water.
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f10-sensors-12-02996: Performance of the proposed algorithm for deep water.

Mentions: In Figure 10, we compare the performance of the proposed range algorithm with the one introduced in [11], and with the algorithms which approximate the inhomogeneous underwater medium as a homogeneous one with a presumably constant sound speed, i.e., we use a straight-line range computation based on the depth information. In this simulation, we consider Gaussian noise for the ToF and depth measurements with a standard deviation (std) of σt = 1 ms and σz = 1 m, respectively. In addition, we choose the deep water environment as a communication medium. The communication is between two points from different layers which are located at depth 550 m and 650 m, respectively. The root mean squared error (RMSE) for the horizontal distance estimation is computed by averaging over 1000 Monte Carlo simulations. As illustrated in this figure, the proposed algorithm performs well for all ranges while the algorithm of [11] has no definite solution from a given point as the horizontal range exceeds a given value. Furthermore, the straight-line algorithm degrades as the distance between the points increases.


Ranging in an underwater medium with multiple isogradient sound speed profile layers.

Ramezani H, Leus G - Sensors (Basel) (2012)

Performance of the proposed algorithm for deep water.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376626&req=5

f10-sensors-12-02996: Performance of the proposed algorithm for deep water.
Mentions: In Figure 10, we compare the performance of the proposed range algorithm with the one introduced in [11], and with the algorithms which approximate the inhomogeneous underwater medium as a homogeneous one with a presumably constant sound speed, i.e., we use a straight-line range computation based on the depth information. In this simulation, we consider Gaussian noise for the ToF and depth measurements with a standard deviation (std) of σt = 1 ms and σz = 1 m, respectively. In addition, we choose the deep water environment as a communication medium. The communication is between two points from different layers which are located at depth 550 m and 650 m, respectively. The root mean squared error (RMSE) for the horizontal distance estimation is computed by averaging over 1000 Monte Carlo simulations. As illustrated in this figure, the proposed algorithm performs well for all ranges while the algorithm of [11] has no definite solution from a given point as the horizontal range exceeds a given value. Furthermore, the straight-line algorithm degrades as the distance between the points increases.

Bottom Line: In this paper, we analyze the problem of acoustic ranging between sensor nodes in an underwater environment.The underwater medium is assumed to be composed of multiple isogradient sound speed profile (SSP) layers where in each layer the sound speed is linearly related to the depth.Furthermore, each sensor node is able to measure its depth and can exchange this information with other nodes.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, The Netherlands. h.mashhadiramezani@tudelft.nl

ABSTRACT
In this paper, we analyze the problem of acoustic ranging between sensor nodes in an underwater environment. The underwater medium is assumed to be composed of multiple isogradient sound speed profile (SSP) layers where in each layer the sound speed is linearly related to the depth. Furthermore, each sensor node is able to measure its depth and can exchange this information with other nodes. Under these assumptions, we first show how the problem of underwater localization can be converted to the traditional range-based terrestrial localization problem when the depth information of the nodes is known a priori. Second, we relate the pair-wise time of flight (ToF) measurements between the nodes to their positions. Next, based on this relation, we propose a novel ranging algorithm for an underwater medium. The proposed ranging algorithm considers reflections from the seabed and sea surface. We will show that even without any reflections, the transmitted signal may travel through more than one path between two given nodes. The proposed algorithm analyzes them and selects the fastest one (first arrival path) based on the measured ToF and the nodes' depth measurements. Finally, in order to evaluate the performance of the proposed algorithm we run several simulations and compare the results with other existing algorithms.

No MeSH data available.


Related in: MedlinePlus