{"title":"A sequential filtering technique for geoacoustic inversion with ship of opportunity and a vector sensor","authors":"Qunyan Ren, J. Hermand","doi":"10.1109/OCEANS.2012.6405067","DOIUrl":null,"url":null,"abstract":"This paper introduces a sequential filtering technique to obtain the ocean bottom acoustic properties with the noise field of a ship of opportunity. It filters the ratio between pressure p and vertical particle velocity Vz (or pressure gradient pg), both measured by a vector sensor, to estimate the environmental properties. This technique models the inverse problem as a random walk for the environmental time/spatial evolution, by formulating the environmental parameters in a recursive state-space form. It assumes the environmental parameters as the summation of previous stage parameters with a noise variance term for each state, and estimates their values along the source ship track by sequentially filtering recorded ship noise data. Numerical tests were carried out for the South East Elba environment. The preliminary results demonstrates this technique can effectively resolve most geoacoustic parameters.","PeriodicalId":434023,"journal":{"name":"2012 Oceans","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Oceans","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANS.2012.6405067","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
This paper introduces a sequential filtering technique to obtain the ocean bottom acoustic properties with the noise field of a ship of opportunity. It filters the ratio between pressure p and vertical particle velocity Vz (or pressure gradient pg), both measured by a vector sensor, to estimate the environmental properties. This technique models the inverse problem as a random walk for the environmental time/spatial evolution, by formulating the environmental parameters in a recursive state-space form. It assumes the environmental parameters as the summation of previous stage parameters with a noise variance term for each state, and estimates their values along the source ship track by sequentially filtering recorded ship noise data. Numerical tests were carried out for the South East Elba environment. The preliminary results demonstrates this technique can effectively resolve most geoacoustic parameters.