{"title":"Three-dimensional acoustic source localization based on multipath time delay in deep ocean.","authors":"Zhen Zhang, Haigang Zhang, Jinshan Fu","doi":"10.1121/10.0039398","DOIUrl":null,"url":null,"abstract":"<p><p>To accurately characterize the non-radial motion of the source relative to the receiver, a three-dimensional (3D) model is essential. The extended Kalman filter (EKF) state matrix is employed to characterize the source's 3D motion. The measurement input for the EKF is the time delay between the direct and surface-reflected arrivals. The differences in the partial derivatives of the distance component have been identified and discussed. Through iterative filtering, a reliable estimate of the source's position in 3D space is obtained. Both simulations and experiments validate the effectiveness of the method, with experimental depth estimation errors within 1.5%.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 10","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JASA express letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1121/10.0039398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ACOUSTICS","Score":null,"Total":0}
引用次数: 0
Abstract
To accurately characterize the non-radial motion of the source relative to the receiver, a three-dimensional (3D) model is essential. The extended Kalman filter (EKF) state matrix is employed to characterize the source's 3D motion. The measurement input for the EKF is the time delay between the direct and surface-reflected arrivals. The differences in the partial derivatives of the distance component have been identified and discussed. Through iterative filtering, a reliable estimate of the source's position in 3D space is obtained. Both simulations and experiments validate the effectiveness of the method, with experimental depth estimation errors within 1.5%.