基于目标窄脉冲激光瞬态特性的隐马尔可夫模型

Yali Hou, Hong Su, Bo Tian, Tie Li
{"title":"基于目标窄脉冲激光瞬态特性的隐马尔可夫模型","authors":"Yali Hou, Hong Su, Bo Tian, Tie Li","doi":"10.1109/ISAPE.2018.8634126","DOIUrl":null,"url":null,"abstract":"Aiming at the fact that the narrow pulse laser transient characteristics of target have not been applied in target recognition, a hidden Markov model (HMM)based on transient characteristics is proposed. For the scattering characteristics of each target in different poses, the reliable model parameters of each target were completed by using the training samples, and each hidden Markov model was established. The maximum likelihood of the test samples for each model was calculated, the target feature class corresponding to the largest probability value was selected as the output category. The result shows that target recognition by hidden Markov model has better performance in terms of calculation speed and accuracy. This method is fast and effective.","PeriodicalId":297368,"journal":{"name":"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hidden Markov Model Based on Target Narrow Pulse Laser Transient Characteristics\",\"authors\":\"Yali Hou, Hong Su, Bo Tian, Tie Li\",\"doi\":\"10.1109/ISAPE.2018.8634126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the fact that the narrow pulse laser transient characteristics of target have not been applied in target recognition, a hidden Markov model (HMM)based on transient characteristics is proposed. For the scattering characteristics of each target in different poses, the reliable model parameters of each target were completed by using the training samples, and each hidden Markov model was established. The maximum likelihood of the test samples for each model was calculated, the target feature class corresponding to the largest probability value was selected as the output category. The result shows that target recognition by hidden Markov model has better performance in terms of calculation speed and accuracy. This method is fast and effective.\",\"PeriodicalId\":297368,\"journal\":{\"name\":\"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAPE.2018.8634126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAPE.2018.8634126","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

针对窄脉冲激光目标瞬态特性在目标识别中尚未得到应用的问题,提出了一种基于瞬态特性的隐马尔可夫模型。针对各目标在不同姿态下的散射特性,利用训练样本完成各目标的可靠模型参数,建立各隐马尔可夫模型。计算每个模型的测试样本的最大似然,选择概率值最大对应的目标特征类作为输出类别。结果表明,基于隐马尔可夫模型的目标识别在计算速度和精度上都有较好的表现。该方法快速有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hidden Markov Model Based on Target Narrow Pulse Laser Transient Characteristics
Aiming at the fact that the narrow pulse laser transient characteristics of target have not been applied in target recognition, a hidden Markov model (HMM)based on transient characteristics is proposed. For the scattering characteristics of each target in different poses, the reliable model parameters of each target were completed by using the training samples, and each hidden Markov model was established. The maximum likelihood of the test samples for each model was calculated, the target feature class corresponding to the largest probability value was selected as the output category. The result shows that target recognition by hidden Markov model has better performance in terms of calculation speed and accuracy. This method is fast and effective.
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