Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation

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dc.contributor.authorZhang, Jiayu
dc.contributor.authorZhang, Tao
dc.contributor.authorShin, Hyosang
dc.contributor.authorWang, Jian
dc.contributor.authorZhang, Chen
dc.date.accessioned2021-04-01T11:15:07Z
dc.date.available2021-04-01T11:15:07Z
dc.date.issued2020-10-30
dc.description.abstractExtensive research results have shown that animals like pigeons and turtles can use geomagnetic information for long-distance migration and homing. This article studies the bionic navigation method inspired by magnetotaxis behavior without prior knowledge. The problem of bionic geomagnetic navigation is generalized as an autonomous search of navigation path under the excitation of geomagnetic environment. The geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation is proposed. In order to optimize the navigation path, the heading angle predicted by the geomagnetic gradient is used to constrain the sample space in the evolutionary algorithm. Then, according to the principle of multiparameter simultaneous convergence, the evaluation function is improved to enhance the reliability and accuracy of the navigation path. Simulations of the algorithm before and after improvement are carried out based on the data retrieved from the enhanced magnetic model (EMM). The performance of the improved method is evaluated and verified in the case of the area with normal geomagnetic field (GF), geomagnetic anomaly area, and multiple destinations. The simulation results show that the search efficiency and the straightness of the navigation path are greatly improved. The reason is that the constraint of sample space reduces the randomness in the process of navigation path search, and the improved evaluation function can evaluate the quality of samples more accurately. The improved algorithm also has good performance in the geomagnetic anomaly area, which indicates the potential application in the future.en_UK
dc.identifier.citationZhang J, Zhang T, Shin HS, et al., (2020) Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation. IEEE Transactions on Instrumentation and Measurement, Volume 70, October 2020, Article number 2503212en_UK
dc.identifier.issn0018-9456
dc.identifier.urihttps://doi.org/10.1109/TIM.2020.3034966
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16538
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectnavigation path searchingen_UK
dc.subjectmultiobjective optimizationen_UK
dc.subjectgeomagnetic field (GF)en_UK
dc.subjectevolutionary algorithmen_UK
dc.subjectBionic geomagnetic navigationen_UK
dc.titleGeomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigationen_UK
dc.typeArticleen_UK

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