中段目标跟踪传感器管理算法研究

Bo Wang, W. An, Yiyu Zhou
{"title":"中段目标跟踪传感器管理算法研究","authors":"Bo Wang, W. An, Yiyu Zhou","doi":"10.1109/IWISA.2009.5073082","DOIUrl":null,"url":null,"abstract":"In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"18 1 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Sensor Management Algorithm of Midcourse Object Tracking\",\"authors\":\"Bo Wang, W. An, Yiyu Zhou\",\"doi\":\"10.1109/IWISA.2009.5073082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.\",\"PeriodicalId\":6327,\"journal\":{\"name\":\"2009 International Workshop on Intelligent Systems and Applications\",\"volume\":\"18 1 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2009.5073082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2009.5073082","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

针对空间跟踪监视系统中连续中段目标跟踪的传感器管理问题,在分析其约束条件的基础上,提出了一种新的优化目标函数。在分析基于二元粒子群优化的传感器管理方法不足的基础上,通过降维和位置向量改进,提出了一种基于实数粒子群优化的传感器管理方法。最后,对经典中段目标跟踪场景进行了仿真,详细比较了几种方法的性能。仿真结果表明,优化后的目标函数能有效地调度传感器;此外,所提出的传感器管理是一种更有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Sensor Management Algorithm of Midcourse Object Tracking
In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.
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