{"title":"基于集群侦察的脉冲雷达信号联合关联、分类与定位","authors":"Yuxin Zhao;Zhanlei Zhu;Hancong Feng;Kailun Tian;Kaili Jiang;Bin Tang","doi":"10.1109/TAES.2025.3543152","DOIUrl":null,"url":null,"abstract":"A significant challenge in cluster collaborative reconnaissance is achieving pulse association between disparate reconnaissance units. However, traditional time-of-arrival (TOA) histogram methods struggle to attain high accuracy in radar pulse association when reconnaissance units are distant, the pulse repetition frequency of the radar signal is high, or the emitter's position is suboptimal. Furthermore, these methods are sensitive to the division of the TOA histogram. To address these issues, we propose a pulse association method for cluster reconnaissance that treats the association, sorting, and localization of radar signals as a unified problem, aiming to solve them collectively. In addition, we introduce the concept of a fuzzy generation set to resolve ambiguities in localization. Simulation results demonstrate that our proposed method significantly enhances the accuracy of pulse association while also achieving high sorting accuracy and localization precision. Under conditions with a TOA error of 50 ns, a site error of 10 m, and a pulse drop rate of 0.2, our proposed method achieves an estimation accuracy exceeding 90% for the emitters count, with pulse association and sorting accuracies greater than 95%, and a localization root-mean-square error of less than 1%.","PeriodicalId":13157,"journal":{"name":"IEEE Transactions on Aerospace and Electronic Systems","volume":"61 4","pages":"8143-8158"},"PeriodicalIF":5.7000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint Pulse Association, Sorting, and Localization of Pulse Radar Signals With Cluster Reconnaissance\",\"authors\":\"Yuxin Zhao;Zhanlei Zhu;Hancong Feng;Kailun Tian;Kaili Jiang;Bin Tang\",\"doi\":\"10.1109/TAES.2025.3543152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A significant challenge in cluster collaborative reconnaissance is achieving pulse association between disparate reconnaissance units. However, traditional time-of-arrival (TOA) histogram methods struggle to attain high accuracy in radar pulse association when reconnaissance units are distant, the pulse repetition frequency of the radar signal is high, or the emitter's position is suboptimal. Furthermore, these methods are sensitive to the division of the TOA histogram. To address these issues, we propose a pulse association method for cluster reconnaissance that treats the association, sorting, and localization of radar signals as a unified problem, aiming to solve them collectively. In addition, we introduce the concept of a fuzzy generation set to resolve ambiguities in localization. Simulation results demonstrate that our proposed method significantly enhances the accuracy of pulse association while also achieving high sorting accuracy and localization precision. Under conditions with a TOA error of 50 ns, a site error of 10 m, and a pulse drop rate of 0.2, our proposed method achieves an estimation accuracy exceeding 90% for the emitters count, with pulse association and sorting accuracies greater than 95%, and a localization root-mean-square error of less than 1%.\",\"PeriodicalId\":13157,\"journal\":{\"name\":\"IEEE Transactions on Aerospace and Electronic Systems\",\"volume\":\"61 4\",\"pages\":\"8143-8158\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-02-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Aerospace and Electronic Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10891702/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Aerospace and Electronic Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10891702/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
Joint Pulse Association, Sorting, and Localization of Pulse Radar Signals With Cluster Reconnaissance
A significant challenge in cluster collaborative reconnaissance is achieving pulse association between disparate reconnaissance units. However, traditional time-of-arrival (TOA) histogram methods struggle to attain high accuracy in radar pulse association when reconnaissance units are distant, the pulse repetition frequency of the radar signal is high, or the emitter's position is suboptimal. Furthermore, these methods are sensitive to the division of the TOA histogram. To address these issues, we propose a pulse association method for cluster reconnaissance that treats the association, sorting, and localization of radar signals as a unified problem, aiming to solve them collectively. In addition, we introduce the concept of a fuzzy generation set to resolve ambiguities in localization. Simulation results demonstrate that our proposed method significantly enhances the accuracy of pulse association while also achieving high sorting accuracy and localization precision. Under conditions with a TOA error of 50 ns, a site error of 10 m, and a pulse drop rate of 0.2, our proposed method achieves an estimation accuracy exceeding 90% for the emitters count, with pulse association and sorting accuracies greater than 95%, and a localization root-mean-square error of less than 1%.
期刊介绍:
IEEE Transactions on Aerospace and Electronic Systems focuses on the organization, design, development, integration, and operation of complex systems for space, air, ocean, or ground environment. These systems include, but are not limited to, navigation, avionics, spacecraft, aerospace power, radar, sonar, telemetry, defense, transportation, automated testing, and command and control.