[1]李睿,王晓丹,蕾蕾,等.一种基于RVM和DS的一维距离像融合识别方法[J].智能系统学报,2016,11(4):554-560.[doi:10.11992/tis.201511021]
LI Rui,WANG Xiaodan,LEI Lei,et al.HRRP fusion recognition by RVM and DS evidence theory[J].CAAI Transactions on Intelligent Systems,2016,11(4):554-560.[doi:10.11992/tis.201511021]
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LI Rui,WANG Xiaodan,LEI Lei,et al.HRRP fusion recognition by RVM and DS evidence theory[J].CAAI Transactions on Intelligent Systems,2016,11(4):554-560.[doi:10.11992/tis.201511021]
一种基于RVM和DS的一维距离像融合识别方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
11
期数:
2016年第4期
页码:
554-560
栏目:
学术论文—机器感知与模式识别
出版日期:
2016-07-25
- Title:
- HRRP fusion recognition by RVM and DS evidence theory
- Keywords:
- target recognition; HRRP; RVM; DS
- 分类号:
- TP181
- 摘要:
- 从如何进一步提升融合识别性能出发，研究有效的高分辨距离像（high range resolution profile，HRRP）融合识别方法。提取了3种平移不变特征，构建了高性能相关向量机（relevance vector machine，RVM）进行特征分类，用DS证据理论融合分类结果以得到目标识别结果，从而提出一种基于RVM和DS的一维距离像融合识别方法。该方法充分利用了RVM输出的概率信息，解决了用DS证据理论进行融合时基本概率赋值获取困难的问题，仿真实验结果表明了本文方法的有效性。
- Abstract:
- Aimed at improving target fusion recognition performance, an efficient approach to radar high resolution range profile (HRRP) fusion recognition is investigated. Three translation-invariant features were extracted from the HRRPs. Meanwhile, a high performance RVM (relevance vector machine) classifier was constructed and DS evidence theory used to fuse the recognition result. A HRRP classification approach, combining RVM and DS evidence theory, is then presented. The method makes full use of RVM output probability information, which solved the difficulty of getting BPA in DS evidence theory. The experimental results based on the simulated data show the effectiveness of the proposed approach.
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备注/Memo
收稿日期:2015-11-23。
基金项目:国家自然科学基金项目（60975026，61273275）.
作者简介:李睿,男,1992年生,硕士研究生,主要研究方向为机器学习、智能信息处理;王晓丹,女,1966年生,教授,博士生导师,主要研究方向为机器学习、智能信息处理。
通讯作者:王晓丹.E-mail:afeu_wang@163.com.
更新日期/Last Update:
1900-01-01