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      The Positioning Accuracy of BAUV Using Fusion of Data from USBL System and Movement Parameters Measurements

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          Abstract

          The article presents a study of the accuracy of estimating the position coordinates of BAUV (Biomimetic Autonomous Underwater Vehicle) by the extended Kalman filter (EKF) method. The fusion of movement parameters measurements and position coordinates fixes was applied. The movement parameters measurements are carried out by on-board navigation devices, while the position coordinates fixes are done by the USBL (Ultra Short Base Line) system. The problem of underwater positioning and the conceptual design of the BAUV navigation system constructed at the Naval Academy (Polish Naval Academy—PNA) are presented in the first part of the paper. The second part consists of description of the evaluation results of positioning accuracy, the genesis of the problem of selecting method for underwater positioning, and the mathematical description of the method of estimating the position coordinates using the EKF method by the fusion of measurements with on-board navigation and measurements obtained with the USBL system. The main part contains a description of experimental research. It consists of a simulation program of navigational parameter measurements carried out during the BAUV passage along the test section. Next, the article covers the determination of position coordinates on the basis of simulated parameters, using EKF and DR methods and the USBL system, which are then subjected to a comparative analysis of accuracy. The final part contains systemic conclusions justifying the desirability of applying the proposed fusion method of navigation parameters for the BAUV positioning.

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          Most cited references31

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          A Kalman Filter Implementation for Precision Improvement in Low-Cost GPS Positioning of Tractors

          Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size, the dimensions of which vary depending on the point of the terrestrial surface. The aim of this study is to reduce the quantization errors of some low-cost GPS receivers by using a Kalman filter. Kinematic tractor model equations were employed to particularize the filter, which was tuned by applying Monte Carlo techniques to eighteen straight trajectories, to select the covariance matrices that produced the lowest Root Mean Square Error in these trajectories. Filter performance was tested by using straight tractor paths, which were either simulated or real trajectories acquired by a GPS receiver. The results show that the filter can reduce the quantization error in distance by around 43%. Moreover, it reduces the standard deviation of the heading by 75%. Data suggest that the proposed filter can satisfactorily preprocess the low-cost GPS receiver data when used in an assistance guidance GPS system for tractors. It could also be useful to smooth tractor GPS trajectories that are sharpened when the tractor moves over rough terrain.
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            Autonomous underwater vehicles for scientific and naval operations

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              An optimization based Moving Horizon Estimation with application to localization of Autonomous Underwater Vehicles

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                15 August 2016
                August 2016
                : 16
                : 8
                : 1279
                Affiliations
                [1 ]Faculty of Navigation and Naval Weapons, Polish Naval Academy, Smidowicza 69, Gdynia 81-103, Poland
                [2 ]Faculty of Civil and Environmental Engineering, Department of Geodesy, Gdansk University of Technology, Narutowicza 11/12, Gdansk 80-233, Poland; aleksander.nowak@ 123456geodezja.pl
                Author notes
                [* ]Correspondence: knaus@ 123456wp.pl ; Tel.: +48-883-911-654
                Article
                sensors-16-01279
                10.3390/s16081279
                5017444
                27537884
                8a349e3b-3c54-4b2e-a593-331c473f56b9
                © 2016 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 May 2016
                : 02 August 2016
                Categories
                Article

                Biomedical engineering
                underwater positioning,estimation of coordinates,autonomous biomimetic underwater vehicle

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