Target Localization and Sensor Synchronization in the Presence of Data Association Uncertainty

Tongyu Ge, R. Tharmarasa, Bernard Lebel, M. Florea, T. Kirubarajan
{"title":"Target Localization and Sensor Synchronization in the Presence of Data Association Uncertainty","authors":"Tongyu Ge, R. Tharmarasa, Bernard Lebel, M. Florea, T. Kirubarajan","doi":"10.23919/fusion43075.2019.9011321","DOIUrl":null,"url":null,"abstract":"In passive sensor networks, sensor registration and data association are two essential processes. Although these two processes affect each other, they are usually addressed separately. In this paper, we propose an algorithm to localize multiple targets and estimate sensor clock biases using time difference of arrival (TDOA) measurements in the presence of data association uncertainty. The problem is formulated as a multidimensional optimization problem, where the objective is to maximize the generalized likelihood of the associated measurements based on target position and sensor clock bias estimates. Computer simulations are carried out to evaluate the performance of the proposed algorithm.","PeriodicalId":348881,"journal":{"name":"2019 22th International Conference on Information Fusion (FUSION)","volume":"1630 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 22th International Conference on Information Fusion (FUSION)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/fusion43075.2019.9011321","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

In passive sensor networks, sensor registration and data association are two essential processes. Although these two processes affect each other, they are usually addressed separately. In this paper, we propose an algorithm to localize multiple targets and estimate sensor clock biases using time difference of arrival (TDOA) measurements in the presence of data association uncertainty. The problem is formulated as a multidimensional optimization problem, where the objective is to maximize the generalized likelihood of the associated measurements based on target position and sensor clock bias estimates. Computer simulations are carried out to evaluate the performance of the proposed algorithm.
数据关联不确定性下的目标定位与传感器同步
在无源传感器网络中,传感器配准和数据关联是两个重要的过程。虽然这两个过程相互影响,但它们通常是分开处理的。在本文中,我们提出了一种算法,在存在数据关联不确定性的情况下,利用到达时间差(TDOA)测量来定位多个目标并估计传感器时钟偏差。该问题被表述为一个多维优化问题,其目标是根据目标位置和传感器时钟偏差估计最大化相关测量的广义似然。通过计算机仿真对所提算法的性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信