基于相互作用多模型粒子滤波的弹道导弹跟踪新方法

Liyun Gong, Miao Yu
{"title":"基于相互作用多模型粒子滤波的弹道导弹跟踪新方法","authors":"Liyun Gong, Miao Yu","doi":"10.1109/ICFSP.2017.8097146","DOIUrl":null,"url":null,"abstract":"This paper proposes a new method for tracking the whole trajectory of a ballistic missile from launch to impact on the ground. Multiple state models are applied for the ballistic missile movement descriptions during different phases, while the transition probabilities are modelled in a state-dependent way. A radar sensor is applied to obtain the missile range, azimuth angle and elevation angle measurements. Based on the state models and measurements, an interacting multiple model based particle filter method is applied for tracking. Simulation studies show that the proposed method outperforms the widely-applied extended Kalman filtering based interacting multiple model for tracking the ballistic missile.","PeriodicalId":382413,"journal":{"name":"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A new interacting multiple model particle filter based ballistic missile tracking method\",\"authors\":\"Liyun Gong, Miao Yu\",\"doi\":\"10.1109/ICFSP.2017.8097146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new method for tracking the whole trajectory of a ballistic missile from launch to impact on the ground. Multiple state models are applied for the ballistic missile movement descriptions during different phases, while the transition probabilities are modelled in a state-dependent way. A radar sensor is applied to obtain the missile range, azimuth angle and elevation angle measurements. Based on the state models and measurements, an interacting multiple model based particle filter method is applied for tracking. Simulation studies show that the proposed method outperforms the widely-applied extended Kalman filtering based interacting multiple model for tracking the ballistic missile.\",\"PeriodicalId\":382413,\"journal\":{\"name\":\"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFSP.2017.8097146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Frontiers of Signal Processing (ICFSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFSP.2017.8097146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

提出了一种跟踪弹道导弹从发射到落地全过程的新方法。采用多状态模型对弹道导弹在不同阶段的运动进行描述,过渡概率以状态依赖的方式建模。采用雷达传感器测量导弹的射程、方位角和仰角。基于状态模型和测量结果,采用基于交互多模型的粒子滤波方法进行跟踪。仿真研究表明,该方法比基于扩展卡尔曼滤波的相互作用多重模型更适合弹道导弹的跟踪。
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
A new interacting multiple model particle filter based ballistic missile tracking method
This paper proposes a new method for tracking the whole trajectory of a ballistic missile from launch to impact on the ground. Multiple state models are applied for the ballistic missile movement descriptions during different phases, while the transition probabilities are modelled in a state-dependent way. A radar sensor is applied to obtain the missile range, azimuth angle and elevation angle measurements. Based on the state models and measurements, an interacting multiple model based particle filter method is applied for tracking. Simulation studies show that the proposed method outperforms the widely-applied extended Kalman filtering based interacting multiple model for tracking the ballistic missile.
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
Online codebook modeling based background subtraction with a moving camera A new interacting multiple model particle filter based ballistic missile tracking method Efficient handoff spectrum scheme using fuzzy decision making in cognitive radio system Emotion recognition system based on physiological signals with Raspberry Pi III implementation Random forests based recognition of the clinical labels using brain MRI scans
×
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