{"title":"在 NLOS 环境中使用无人飞行器进行多波源定位","authors":"Shinichi Murata;Takahiro Matsuda;Takefumi Hiraguri","doi":"10.23919/comex.2024XBL0104","DOIUrl":null,"url":null,"abstract":"Localization techniques for unknown radio wave sources are crucial from the perspective of efficient utilization of frequency resources. The authors have studied methods for localizing a single wave source using unmanned aerial vehicles (UAVs) in non-line-of-sight (NLOS) environments based on maximum likelihood estimation. In this study, we propose a localization method for multiple wave sources by extending the singlewave source localization method. In the proposed method, the direction of arrivals (DoAs) at UAVs is modeled with a mixture of von-Mises distributions, and the wave sources are estimated by superimposing the DoA distributions estimated at the UAVs. The proposed method is validated with a simple simulation experiment with two wave sources.","PeriodicalId":54101,"journal":{"name":"IEICE Communications Express","volume":"13 9","pages":"375-378"},"PeriodicalIF":0.3000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10591715","citationCount":"0","resultStr":"{\"title\":\"Multiple-Wave Source Localization Using UAVs in NLOS Environments\",\"authors\":\"Shinichi Murata;Takahiro Matsuda;Takefumi Hiraguri\",\"doi\":\"10.23919/comex.2024XBL0104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Localization techniques for unknown radio wave sources are crucial from the perspective of efficient utilization of frequency resources. The authors have studied methods for localizing a single wave source using unmanned aerial vehicles (UAVs) in non-line-of-sight (NLOS) environments based on maximum likelihood estimation. In this study, we propose a localization method for multiple wave sources by extending the singlewave source localization method. In the proposed method, the direction of arrivals (DoAs) at UAVs is modeled with a mixture of von-Mises distributions, and the wave sources are estimated by superimposing the DoA distributions estimated at the UAVs. The proposed method is validated with a simple simulation experiment with two wave sources.\",\"PeriodicalId\":54101,\"journal\":{\"name\":\"IEICE Communications Express\",\"volume\":\"13 9\",\"pages\":\"375-378\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10591715\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEICE Communications Express\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10591715/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Communications Express","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10591715/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
从有效利用频率资源的角度来看,未知无线电波源的定位技术至关重要。作者们研究了在非视距(NLOS)环境下使用无人飞行器(UAV)基于最大似然估计对单个波源进行定位的方法。在本研究中,我们通过扩展单波源定位方法,提出了一种多波源定位方法。在所提出的方法中,无人机的到达方向(DoA)用冯-米塞斯分布的混合物建模,波源则通过叠加无人机上估计的 DoA 分布来估计。利用两个波源的简单模拟实验验证了所提出的方法。
Multiple-Wave Source Localization Using UAVs in NLOS Environments
Localization techniques for unknown radio wave sources are crucial from the perspective of efficient utilization of frequency resources. The authors have studied methods for localizing a single wave source using unmanned aerial vehicles (UAVs) in non-line-of-sight (NLOS) environments based on maximum likelihood estimation. In this study, we propose a localization method for multiple wave sources by extending the singlewave source localization method. In the proposed method, the direction of arrivals (DoAs) at UAVs is modeled with a mixture of von-Mises distributions, and the wave sources are estimated by superimposing the DoA distributions estimated at the UAVs. The proposed method is validated with a simple simulation experiment with two wave sources.