{"title":"基于半确定规划的水下定位与跟踪","authors":"Dexin Wang, Liuqing Yang, Xiang Cheng","doi":"10.1109/ICSPCC.2013.6664147","DOIUrl":null,"url":null,"abstract":"In underwater localization, buoyed anchors are preferable because of their low cost and the convenience to deploy, calibrate and reuse. However, this setup imposes extra difficulty to the localization of submerged targets since they are outside of the convex hull formed by the anchors. In this paper, we propose a semi-definite programming (SDP) based localization approach that is augmented by measurements obtained via onboard pressure sensors. Compared with the widely-adopted linearized least squares solution, simulations show our augmented SDP offers improved accuracy for point localization and faster convergence for tracking, under the same system configuration and environmental conditions, especially at low signal to noise ratio (SNR).","PeriodicalId":124509,"journal":{"name":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Underwater localization and tracking based on semi-definite programming\",\"authors\":\"Dexin Wang, Liuqing Yang, Xiang Cheng\",\"doi\":\"10.1109/ICSPCC.2013.6664147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In underwater localization, buoyed anchors are preferable because of their low cost and the convenience to deploy, calibrate and reuse. However, this setup imposes extra difficulty to the localization of submerged targets since they are outside of the convex hull formed by the anchors. In this paper, we propose a semi-definite programming (SDP) based localization approach that is augmented by measurements obtained via onboard pressure sensors. Compared with the widely-adopted linearized least squares solution, simulations show our augmented SDP offers improved accuracy for point localization and faster convergence for tracking, under the same system configuration and environmental conditions, especially at low signal to noise ratio (SNR).\",\"PeriodicalId\":124509,\"journal\":{\"name\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCC.2013.6664147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC.2013.6664147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Underwater localization and tracking based on semi-definite programming
In underwater localization, buoyed anchors are preferable because of their low cost and the convenience to deploy, calibrate and reuse. However, this setup imposes extra difficulty to the localization of submerged targets since they are outside of the convex hull formed by the anchors. In this paper, we propose a semi-definite programming (SDP) based localization approach that is augmented by measurements obtained via onboard pressure sensors. Compared with the widely-adopted linearized least squares solution, simulations show our augmented SDP offers improved accuracy for point localization and faster convergence for tracking, under the same system configuration and environmental conditions, especially at low signal to noise ratio (SNR).