基于自适应多模型滤波的ADS-B系统轨迹跟踪

Kai-Ge Zhang, Yu-Long Qiao, Chaozhu Zhang
{"title":"基于自适应多模型滤波的ADS-B系统轨迹跟踪","authors":"Kai-Ge Zhang, Yu-Long Qiao, Chaozhu Zhang","doi":"10.1109/RVSP.2013.28","DOIUrl":null,"url":null,"abstract":"ADS-B is a cooperating surveillance technology which can broadcast not only the position messages, but also the velocity, status and TCP (Trajectory Change Point) which could be used for target surveillance. This paper tries to utilize the multi-model method to enhance the filtering function. Through the simulation, we find it is reasonable to use the multi-model method and we also propose the unified modes structure which will benefit the computing efficiency and the parameter auto-adaptive modulation.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"21 1","pages":"93-97"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trajectory Tracking Using Auto-adaptive Multi-model Filtering Method in ADS-B System\",\"authors\":\"Kai-Ge Zhang, Yu-Long Qiao, Chaozhu Zhang\",\"doi\":\"10.1109/RVSP.2013.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ADS-B is a cooperating surveillance technology which can broadcast not only the position messages, but also the velocity, status and TCP (Trajectory Change Point) which could be used for target surveillance. This paper tries to utilize the multi-model method to enhance the filtering function. Through the simulation, we find it is reasonable to use the multi-model method and we also propose the unified modes structure which will benefit the computing efficiency and the parameter auto-adaptive modulation.\",\"PeriodicalId\":6585,\"journal\":{\"name\":\"2013 Second International Conference on Robot, Vision and Signal Processing\",\"volume\":\"21 1\",\"pages\":\"93-97\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Second International Conference on Robot, Vision and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RVSP.2013.28\",\"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 Second International Conference on Robot, Vision and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RVSP.2013.28","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

ADS-B是一种协作监视技术,它不仅可以广播位置信息,还可以广播速度、状态和TCP(弹道变化点)信息,可用于目标监视。本文尝试利用多模型方法来增强滤波功能。通过仿真,我们发现采用多模型方法是合理的,并提出了统一的模式结构,有利于提高计算效率和参数自适应调制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trajectory Tracking Using Auto-adaptive Multi-model Filtering Method in ADS-B System
ADS-B is a cooperating surveillance technology which can broadcast not only the position messages, but also the velocity, status and TCP (Trajectory Change Point) which could be used for target surveillance. This paper tries to utilize the multi-model method to enhance the filtering function. Through the simulation, we find it is reasonable to use the multi-model method and we also propose the unified modes structure which will benefit the computing efficiency and the parameter auto-adaptive modulation.
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
×
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