{"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}
引用次数: 0
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.
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。