scholarly journals Range-only underwater target localization: Path characterization

2016 ◽  
Author(s):  
I. Masmitja ◽  
S. Gomariz ◽  
J. Del Rio ◽  
B. Kieft ◽  
T. O'Reilly
Keyword(s):  
Target Localization ◽  
Underwater Target

Underwater Target Localization

2010 ◽  
Vol 17 (1) ◽  
pp. 64-70 ◽  
Author(s):  
Giacomo Marani ◽  
Song Choi
Keyword(s):  
Target Localization ◽  
Underwater Target

scholarly journals Multiple underwater target positioning with optimally placed acoustic surface sensor networks

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877323 ◽  
Author(s):  
David Moreno-Salinas ◽  
Antonio Manuel Pascoal ◽  
Joaquín Aranda
Keyword(s):  
Autonomous Vehicles ◽  
Information Matrix ◽  
Sensor Placement ◽  
Target Localization ◽  
Sensor Nodes ◽  
Multiple Objective ◽  
Positioning Accuracy ◽  
Trade Offs ◽  
Sensor Configuration ◽  
Underwater Target

In an increasing number of scientific and commercial mission scenarios at sea, it is required to simultaneously localize a group of underwater targets. The latter may include moored systems, autonomous vehicles, and even human divers. For reasons that have to do with the unavailability of Global Positioning System underwater, cost reduction, and simplicity of operation, there is currently a surge of interest in the development of range-based multiple target localization systems that rely on the computation of the distances between the targets and a number of sensor nodes deployed at the ocean surface, equipped with acoustic range measuring devices. In the case of a single target, there is a wealth of literature on the problem of optimal acoustic sensor placement to maximize the information available for target localization using trilateration methods. In the case of multiple targets, however, the literature is scarce. Motivated by these considerations, we address the problem of optimal sensor placement for multiple underwater target positioning. In this setup, we are naturally led to a multiple objective optimization problem, the solution of which allows for the analysis of the trade-offs involved in the localization of the targets simultaneously. To this end, we resort to tools from estimation theory and multi-objective optimization. For each target, the function to be minimized (by proper choice of the sensor configuration) is related to the determinant of the corresponding Fisher information matrix, which yields information on the minimum possible covariance of the error with which the position of the target can be estimated using any non-biased estimator. To deal with the fact that more than one target is involved, we exploit the concept of multiple objective Pareto-optimal solutions to characterize the best possible accuracy with which each of the targets can be positioned, given constraints on the desired positioning accuracy of the other targets. Simulation examples illustrate how, for a three-sensor network and two targets, it is possible to define an optimal sensor configuration that yields large positioning accuracy for both targets simultaneously, using convex optimization tools. When more than two targets are involved, however, more than three sensors are required to exploit an adequate trade-off of the accuracy with which each target can be positioned by resorting to non-convex and Pareto-optimization tools. We show how in this case the optimal sensor configurations depend on the Pareto weights assigned to each of the targets, as well as on the number of sensors, the number of targets, and the uncertainty with which the positions of the targets are known a priori.

scholarly journals Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1976 ◽  
Author(s):  
Chaofeng He ◽  
Yiyin Wang ◽  
Wenbin Yu ◽  
Lei Song
Keyword(s):  
Sound Speed ◽  
Time Synchronization ◽  
Target Localization ◽  
Underwater Sound ◽  
Central Receiver ◽  
Sonar System ◽  
Input Multiple Output ◽  
Single Input ◽  
Underwater Target ◽  
Hostile Environments

A distributed single-input multiple-output (SIMO) sonar system is composed of a sound source and multiple underwater receivers. It provides an important framework for underwater target localization. However, underwater hostile environments bring more challenges for underwater target localization than terrestrial target localization, such as the difficulties of synchronizing all the underwater receiver clocks, the varying underwater sound speed and the uncertainties of the locations of the underwater receivers. In this paper, we take the sound speed variation, the time synchronization and the uncertainties of the receiver locations into account, and propose the underwater target localization and synchronization (UTLS) algorithm for the distributed SIMO sonar system. In the distributed SIMO sonar system, the receivers are organized in a star topology, where the information fusion is carried out in the central receiver (CR). All the receivers are not synchronized and their positions are known with uncertainties. Moreover, the underwater sound speed is approximately modeled by a depth-dependent sound speed profile (SSP). We evaluate our proposed UTLS algorithm by comparing it with several benchmark algorithms via numerical simulations. The simulation results reveal the superiority of our proposed UTLS algorithm.

Underwater target localization using long baseline positioning system

2016 ◽  
Vol 111 ◽  
pp. 129-134 ◽  
Author(s):  
Jucheng Zhang ◽  
Yunfeng Han ◽  
Cuie Zheng ◽  
Dajun Sun
Keyword(s):  
Target Localization ◽  
Positioning System ◽  
Long Baseline ◽  
Underwater Target

scholarly journals Underwater Target Localization using the Generalized Lloyd-Mirror Pattern

2021 ◽  
Vol 15 (3) ◽  
pp. 17-24
Author(s):  
Mojgan Mirzaei Hotkani ◽  
Seyed Alireza Seyedin ◽  
Jean Francois Bousquet
Keyword(s):  
Target Localization ◽  
Underwater Target
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