基于TDOA-DOA融合算法的多无人机协同无源定位

X. Liu, Ju Jiang, Zhe Zhang
{"title":"基于TDOA-DOA融合算法的多无人机协同无源定位","authors":"X. Liu, Ju Jiang, Zhe Zhang","doi":"10.1109/ISAS59543.2023.10164550","DOIUrl":null,"url":null,"abstract":"Electronic warfare plays an essential role in modern warfare. In this background, the multiple UAVs cooperative passive positioning technology, which has the advantages of long operating distance and strong concealment, has received significant attention. Considering the scenario of three UAVs attacking enemy surface ships in a naval battle, this paper proposes a collaborative passive localization algorithm based on TDOA and DOA to solve the positioning problem in three-dimensional space. Firstly, we establish a passive location model according to the time delay and measurement errors of the ship target and UAV. Second, the nonlinear terms are linearized using the relative spatial position between the ship and the UAV. Third, a loss function is constructed for the error term, and the least square estimation algorithm obtains the ship coordinate position. Finally, we design two comparative experiments. One discusses the influence of acute angle, isosceles, right angle, equilateral and obtuse angle five UAV spatial structures on positioning accuracy; the other explores the impact of different delay and measurement errors on positioning accuracy. The numerical simulation results effectively verify the model’s rationality and the algorithm’s effectiveness.","PeriodicalId":199115,"journal":{"name":"2023 6th International Symposium on Autonomous Systems (ISAS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative Passive Location of Multi-UAVs Based on TDOA-DOA Fusion Algorithm\",\"authors\":\"X. Liu, Ju Jiang, Zhe Zhang\",\"doi\":\"10.1109/ISAS59543.2023.10164550\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electronic warfare plays an essential role in modern warfare. In this background, the multiple UAVs cooperative passive positioning technology, which has the advantages of long operating distance and strong concealment, has received significant attention. Considering the scenario of three UAVs attacking enemy surface ships in a naval battle, this paper proposes a collaborative passive localization algorithm based on TDOA and DOA to solve the positioning problem in three-dimensional space. Firstly, we establish a passive location model according to the time delay and measurement errors of the ship target and UAV. Second, the nonlinear terms are linearized using the relative spatial position between the ship and the UAV. Third, a loss function is constructed for the error term, and the least square estimation algorithm obtains the ship coordinate position. Finally, we design two comparative experiments. One discusses the influence of acute angle, isosceles, right angle, equilateral and obtuse angle five UAV spatial structures on positioning accuracy; the other explores the impact of different delay and measurement errors on positioning accuracy. The numerical simulation results effectively verify the model’s rationality and the algorithm’s effectiveness.\",\"PeriodicalId\":199115,\"journal\":{\"name\":\"2023 6th International Symposium on Autonomous Systems (ISAS)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 6th International Symposium on Autonomous Systems (ISAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAS59543.2023.10164550\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 6th International Symposium on Autonomous Systems (ISAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAS59543.2023.10164550","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

电子战在现代战争中起着重要的作用。在此背景下,多无人机协同无源定位技术以其作战距离远、隐蔽性强等优点受到了广泛关注。针对海战中三架无人机攻击敌方水面舰艇的场景,提出了一种基于TDOA和DOA的协同被动定位算法,解决了三维空间中的定位问题。首先,根据舰船目标和无人机的时延和测量误差建立被动定位模型;其次,利用舰船与无人机之间的相对空间位置对非线性项进行线性化处理。第三,对误差项构造损失函数,利用最小二乘估计算法得到船舶坐标位置;最后,我们设计了两个对比实验。讨论了锐角、等腰、直角、等边和钝角五种无人机空间结构对定位精度的影响;二是探讨不同时延和测量误差对定位精度的影响。数值仿真结果有效地验证了模型的合理性和算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Cooperative Passive Location of Multi-UAVs Based on TDOA-DOA Fusion Algorithm
Electronic warfare plays an essential role in modern warfare. In this background, the multiple UAVs cooperative passive positioning technology, which has the advantages of long operating distance and strong concealment, has received significant attention. Considering the scenario of three UAVs attacking enemy surface ships in a naval battle, this paper proposes a collaborative passive localization algorithm based on TDOA and DOA to solve the positioning problem in three-dimensional space. Firstly, we establish a passive location model according to the time delay and measurement errors of the ship target and UAV. Second, the nonlinear terms are linearized using the relative spatial position between the ship and the UAV. Third, a loss function is constructed for the error term, and the least square estimation algorithm obtains the ship coordinate position. Finally, we design two comparative experiments. One discusses the influence of acute angle, isosceles, right angle, equilateral and obtuse angle five UAV spatial structures on positioning accuracy; the other explores the impact of different delay and measurement errors on positioning accuracy. The numerical simulation results effectively verify the model’s rationality and the algorithm’s effectiveness.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A new type of video text automatic recognition method and its application in film and television works H∞ state feedback control for fuzzy singular Markovian jump systems with constant time delays and impulsive perturbations MMSTP: Multi-modal Spatiotemporal Feature Fusion Network for Precipitation Prediction Digital twin based bearing fault simulation modeling strategy and display dynamics End-to-End Model-Based Gait Recognition with Matching Module Based on Graph Neural Networks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1