具有时间相关性的复合分布的鲁棒性能预测建模

L. Rosenberg, S. Bocquet
{"title":"具有时间相关性的复合分布的鲁棒性能预测建模","authors":"L. Rosenberg, S. Bocquet","doi":"10.1109/RADAR.2013.6652019","DOIUrl":null,"url":null,"abstract":"Robustly predicting target detection performance in temporally correlated clutter with a fluctuating target has proven to be a difficult problem. If the correlation is not accounted for in a radar model, the required signal to interference ratio for a given probability of detection, Pd, could be incorrect by several dB, resulting in over-estimated performance. This paper describes a robust method for calculating the Pd for K, KK and Pareto compound distributions. Results are then presented using realistic parameter models for high grazing angle sea-clutter.","PeriodicalId":365285,"journal":{"name":"2013 International Conference on Radar","volume":"240 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Robust performance prediction modelling for compound distributions with temporal correlation\",\"authors\":\"L. Rosenberg, S. Bocquet\",\"doi\":\"10.1109/RADAR.2013.6652019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Robustly predicting target detection performance in temporally correlated clutter with a fluctuating target has proven to be a difficult problem. If the correlation is not accounted for in a radar model, the required signal to interference ratio for a given probability of detection, Pd, could be incorrect by several dB, resulting in over-estimated performance. This paper describes a robust method for calculating the Pd for K, KK and Pareto compound distributions. Results are then presented using realistic parameter models for high grazing angle sea-clutter.\",\"PeriodicalId\":365285,\"journal\":{\"name\":\"2013 International Conference on Radar\",\"volume\":\"240 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Radar\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2013.6652019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Radar","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2013.6652019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

在具有波动目标的时间相关杂波条件下,对目标检测性能进行鲁棒预测已被证明是一个难题。如果在雷达模型中没有考虑到相关性,则给定探测概率Pd所需的信干扰比可能不正确几个dB,从而导致高估性能。本文描述了一种计算K、KK和Pareto复合分布的Pd的鲁棒方法。然后给出了高掠角海杂波的真实参数模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust performance prediction modelling for compound distributions with temporal correlation
Robustly predicting target detection performance in temporally correlated clutter with a fluctuating target has proven to be a difficult problem. If the correlation is not accounted for in a radar model, the required signal to interference ratio for a given probability of detection, Pd, could be incorrect by several dB, resulting in over-estimated performance. This paper describes a robust method for calculating the Pd for K, KK and Pareto compound distributions. Results are then presented using realistic parameter models for high grazing angle sea-clutter.
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