Dezert-Smarandache理论下融合一次雷达、二次监视雷达和ESM传感器属性信息分析

Tadeusz Pietkiewicz, A. Kawalec, B. Wajszczyk
{"title":"Dezert-Smarandache理论下融合一次雷达、二次监视雷达和ESM传感器属性信息分析","authors":"Tadeusz Pietkiewicz, A. Kawalec, B. Wajszczyk","doi":"10.23919/IRS.2017.8008199","DOIUrl":null,"url":null,"abstract":"This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section is adopted the basic taxonomy of attribute identification in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The last values can be interpreted as a conjunction of basic valus. The basis of theoretical considerations is the Dezert-Smarandache theory of inference. The following combining rules are presented: the classical and hybrid Dezert-Smarandache rules and the Proportional Conflict Redistribution #5 (PCR5).The basic belief assignment for primary and secondary radars has been taken from [14]. In the next section rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. The emitter DB has a lot of records for any class of emitter. Signal parameters vector recognition is based on finding the nearest center of emitter parameters cluster. The basic belief assignment (bba) of different attribute identification values for ESM sensor has been defined. Each sensor report sent to the fusion information center contains a vector of belief mass of attribute identification. Results of the PCR#5 sensor information combining method are presented in the final part of the paper. At the end of the paper conclusions are given. They confirm the legitimacy of the use of the Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.","PeriodicalId":430241,"journal":{"name":"2017 18th International Radar Symposium (IRS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Analysis of fusion primary radar, secondary surveillance radar (IFF) and ESM sensor attribute information under Dezert-Smarandache theory\",\"authors\":\"Tadeusz Pietkiewicz, A. Kawalec, B. Wajszczyk\",\"doi\":\"10.23919/IRS.2017.8008199\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section is adopted the basic taxonomy of attribute identification in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The last values can be interpreted as a conjunction of basic valus. The basis of theoretical considerations is the Dezert-Smarandache theory of inference. The following combining rules are presented: the classical and hybrid Dezert-Smarandache rules and the Proportional Conflict Redistribution #5 (PCR5).The basic belief assignment for primary and secondary radars has been taken from [14]. In the next section rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. The emitter DB has a lot of records for any class of emitter. Signal parameters vector recognition is based on finding the nearest center of emitter parameters cluster. The basic belief assignment (bba) of different attribute identification values for ESM sensor has been defined. Each sensor report sent to the fusion information center contains a vector of belief mass of attribute identification. Results of the PCR#5 sensor information combining method are presented in the final part of the paper. At the end of the paper conclusions are given. They confirm the legitimacy of the use of the Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.\",\"PeriodicalId\":430241,\"journal\":{\"name\":\"2017 18th International Radar Symposium (IRS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 18th International Radar Symposium (IRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/IRS.2017.8008199\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 18th International Radar Symposium (IRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IRS.2017.8008199","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

本文提出了一种融合主辅联合监视雷达和电子保障措施两种传感器提供的识别(属性)信息的方法。第一部分根据STANAG 1241第5版和STANAG 1241第6版(草案)的标准,采用了属性识别的基本分类。这些标准提供了以下属性标识的基本值:FRIEND、HOSTILE、NEUTRAL、UNKNOWN和附加值:ASSUMED FRIEND和SUSPECT。最后的值可以解释为基本值的结合。理论考虑的基础是Dezert-Smarandache推理理论。提出了以下组合规则:经典和混合Dezert-Smarandache规则和比例冲突再分配#5 (PCR5)。初级和次级雷达的基本信念赋值取自[14]。下一节给出了装备雷达辐射源数据库的ESM传感器确定属性信息的规则。发射器DB对任何类型的发射器都有大量记录。信号参数矢量识别是基于寻找最近的辐射源参数簇中心。定义了ESM传感器不同属性识别值的基本信念分配(bba)。发送到融合信息中心的每个传感器报告都包含一个属性识别置信质量向量。最后给出了PCR#5传感器信息组合方法的结果。论文最后给出了结论。他们证实了将Dezert-Smarandache理论用于初级雷达、次级雷达和ESM传感器信息融合的合法性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of fusion primary radar, secondary surveillance radar (IFF) and ESM sensor attribute information under Dezert-Smarandache theory
This paper presents a method of fusion of identification (attribute) information provided by two types of sensors: combined primary and secondary (IFF) surveillance radars and ESM (Electronic Support Measures). In the first section is adopted the basic taxonomy of attribute identification in accordance with the standards of STANAG 1241 ed. 5 and STANAG 1241 ed. 6 (draft). These standards provide the following basic values of the attribute identifications: FRIEND, HOSTILE, NEUTRAL, UNKNOWN and additional values: ASSUMED FRIEND and SUSPECT. The last values can be interpreted as a conjunction of basic valus. The basis of theoretical considerations is the Dezert-Smarandache theory of inference. The following combining rules are presented: the classical and hybrid Dezert-Smarandache rules and the Proportional Conflict Redistribution #5 (PCR5).The basic belief assignment for primary and secondary radars has been taken from [14]. In the next section rules of determining attribute information by ESM sensor equipped with the data base of radar emitters are presented. The emitter DB has a lot of records for any class of emitter. Signal parameters vector recognition is based on finding the nearest center of emitter parameters cluster. The basic belief assignment (bba) of different attribute identification values for ESM sensor has been defined. Each sensor report sent to the fusion information center contains a vector of belief mass of attribute identification. Results of the PCR#5 sensor information combining method are presented in the final part of the paper. At the end of the paper conclusions are given. They confirm the legitimacy of the use of the Dezert-Smarandache theory into information fusion for primary radars, secondary radars and ESM sensors.
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