Multi-feature fusion for target recognition based on improved D-S evidence iterative discount method

Caiyun Wang, Shuxia Wu, Zhiyong He
{"title":"Multi-feature fusion for target recognition based on improved D-S evidence iterative discount method","authors":"Caiyun Wang, Shuxia Wu, Zhiyong He","doi":"10.23919/URSIGASS.2017.8105262","DOIUrl":null,"url":null,"abstract":"A new multi-feature fusion method is proposed for the radar target recognition based on D-S evidence iterative discount method. Firstly, the discount factor is defined based on the multi-feature confusion matrix and basic probability assignment (BPA) function. Then, when the conflict is high, the evidence is discounted using the discount factor, and basic probability assignment function, discount factor and conflict coefficient are updated; repeat the above discounts procedure and stop the evidence source correction when the evidence conflict coefficient is less than the threshold. Finally, fusion recognition is achieved by using the revised evidence. Compared with the other fusion recognition algorithm, the simulation results show that this proposed algorithm performs better.","PeriodicalId":377869,"journal":{"name":"2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/URSIGASS.2017.8105262","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

A new multi-feature fusion method is proposed for the radar target recognition based on D-S evidence iterative discount method. Firstly, the discount factor is defined based on the multi-feature confusion matrix and basic probability assignment (BPA) function. Then, when the conflict is high, the evidence is discounted using the discount factor, and basic probability assignment function, discount factor and conflict coefficient are updated; repeat the above discounts procedure and stop the evidence source correction when the evidence conflict coefficient is less than the threshold. Finally, fusion recognition is achieved by using the revised evidence. Compared with the other fusion recognition algorithm, the simulation results show that this proposed algorithm performs better.
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
基于改进D-S证据迭代折现法的多特征融合目标识别
提出了一种基于D-S证据迭代折现法的雷达目标识别多特征融合新方法。首先,基于多特征混淆矩阵和基本概率分配(BPA)函数定义折现因子;然后,在冲突较大时,利用折现因子对证据进行折现,更新基本概率赋值函数、折现因子和冲突系数;重复上述折扣过程,当证据冲突系数小于阈值时,停止证据源校正。最后,利用修正后的证据实现融合识别。仿真结果表明,与其他融合识别算法相比,该算法具有更好的性能。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Visible light communication based on offset pulse position modulation (Offset-PPM) using high power LED Measurement, simulation and optimization of wideband log-periodic antennas Time-frequency diversity measurements in power systems Diagnostic potential of free-space radiometric partial discharge measurements Low power embedded processing of scintillation events with silicon photo multipliers
×
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