{"title":"Determination of Vessel Heading using Magnetic Wake Imaging","authors":"M. Fallah, M. Monemi","doi":"10.52547/ijcoe.5.3.19","DOIUrl":null,"url":null,"abstract":"Article History: Received: 03 Mar. 2020 Accepted: 29 June. 2021 The small microwave skin depth of sea water as well as the small penetration depth of laser signal in water impose limitations on the application of SAR and Lidar in sea surveillance systems. On the other hand, vessels travelling at sea bring about hydrodynamic anomalies in the sea water called as wake. These hydrodynamic disturbances can be detected by using some techniques such as airborne radio imaging and Extremely Low Frequency (ELF) electromagnetic signal processing. In practice, the motion of conductive sea water anomalies in the natural earth's magnetic field induces ELF magnetic wakes which can be measured via accurate magnetic sensors and detected through signal processing schemes. The physical properties of the hydrodynamic wake as well as those relating to the corresponding magnetic wake are directly related to the vessel parameters such as hull shape, speed and heading. In this work, we firstly derive and formulate the mathematical expressions relating to the aforementioned hydrodynamic and magnetic wakes. By employing derived expressions, a novel detection scheme is proposed based on constructing the 2-dimentional image of the vessel’s magnetic wake through the magnetic signals captured from an array of magnetic sensors, and finally, the relation between the spectral image of the magnetic wake and the vessel heading is studied. We will show that our proposed scheme can detect the existence of a remote vessel as well as its heading from the constructed image with high accuracy, and moreover, it does not have common limitations of existing single-sensor based heading detection schemes.","PeriodicalId":33914,"journal":{"name":"International Journal of Coastal and Offshore Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Coastal and Offshore Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52547/ijcoe.5.3.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Article History: Received: 03 Mar. 2020 Accepted: 29 June. 2021 The small microwave skin depth of sea water as well as the small penetration depth of laser signal in water impose limitations on the application of SAR and Lidar in sea surveillance systems. On the other hand, vessels travelling at sea bring about hydrodynamic anomalies in the sea water called as wake. These hydrodynamic disturbances can be detected by using some techniques such as airborne radio imaging and Extremely Low Frequency (ELF) electromagnetic signal processing. In practice, the motion of conductive sea water anomalies in the natural earth's magnetic field induces ELF magnetic wakes which can be measured via accurate magnetic sensors and detected through signal processing schemes. The physical properties of the hydrodynamic wake as well as those relating to the corresponding magnetic wake are directly related to the vessel parameters such as hull shape, speed and heading. In this work, we firstly derive and formulate the mathematical expressions relating to the aforementioned hydrodynamic and magnetic wakes. By employing derived expressions, a novel detection scheme is proposed based on constructing the 2-dimentional image of the vessel’s magnetic wake through the magnetic signals captured from an array of magnetic sensors, and finally, the relation between the spectral image of the magnetic wake and the vessel heading is studied. We will show that our proposed scheme can detect the existence of a remote vessel as well as its heading from the constructed image with high accuracy, and moreover, it does not have common limitations of existing single-sensor based heading detection schemes.