{"title":"用于旋转源定位的模式组成波束成形解卷积","authors":"Ce Zhang, Wei Ma","doi":"10.1007/s42401-024-00297-y","DOIUrl":null,"url":null,"abstract":"<div><p>Mode composition beamforming (MCB) is a frequency-domain rotating beamforming method for rotating acoustic source localization. Compared with other rotating beamforming methods, MCB has both wide applicability and high computational efficiency. The expression for MCB in literature is however not suitable for the application of deconvolution algorithms, which limits further improvements of dynamic range and spatial resolution of MCB. In this work, application of deconvolution algorithms to MCB is investigated. Firstly, the expression of MCB is transformed into a matrix form. Then the deconvolution algorithms of MCB, including DAMAS and CLEAN-SC, are derived based on the matrix form of MCB. Nextly the deconvolution algorithms of MCB are verified through a benchmark simulation case. Lastly deconvolution algorithms of MCB are applied in a phased array measurement for the rotor of an unmanned aerial vehicle to improve the dynamic range and spatial resolution of rotating source localization.</p></div>","PeriodicalId":36309,"journal":{"name":"Aerospace Systems","volume":"7 4","pages":"727 - 734"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s42401-024-00297-y.pdf","citationCount":"0","resultStr":"{\"title\":\"Deconvolution of mode composition beamforming for rotating source localization\",\"authors\":\"Ce Zhang, Wei Ma\",\"doi\":\"10.1007/s42401-024-00297-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mode composition beamforming (MCB) is a frequency-domain rotating beamforming method for rotating acoustic source localization. Compared with other rotating beamforming methods, MCB has both wide applicability and high computational efficiency. The expression for MCB in literature is however not suitable for the application of deconvolution algorithms, which limits further improvements of dynamic range and spatial resolution of MCB. In this work, application of deconvolution algorithms to MCB is investigated. Firstly, the expression of MCB is transformed into a matrix form. Then the deconvolution algorithms of MCB, including DAMAS and CLEAN-SC, are derived based on the matrix form of MCB. Nextly the deconvolution algorithms of MCB are verified through a benchmark simulation case. Lastly deconvolution algorithms of MCB are applied in a phased array measurement for the rotor of an unmanned aerial vehicle to improve the dynamic range and spatial resolution of rotating source localization.</p></div>\",\"PeriodicalId\":36309,\"journal\":{\"name\":\"Aerospace Systems\",\"volume\":\"7 4\",\"pages\":\"727 - 734\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s42401-024-00297-y.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aerospace Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s42401-024-00297-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace Systems","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s42401-024-00297-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Deconvolution of mode composition beamforming for rotating source localization
Mode composition beamforming (MCB) is a frequency-domain rotating beamforming method for rotating acoustic source localization. Compared with other rotating beamforming methods, MCB has both wide applicability and high computational efficiency. The expression for MCB in literature is however not suitable for the application of deconvolution algorithms, which limits further improvements of dynamic range and spatial resolution of MCB. In this work, application of deconvolution algorithms to MCB is investigated. Firstly, the expression of MCB is transformed into a matrix form. Then the deconvolution algorithms of MCB, including DAMAS and CLEAN-SC, are derived based on the matrix form of MCB. Nextly the deconvolution algorithms of MCB are verified through a benchmark simulation case. Lastly deconvolution algorithms of MCB are applied in a phased array measurement for the rotor of an unmanned aerial vehicle to improve the dynamic range and spatial resolution of rotating source localization.
期刊介绍：
Aerospace Systems provides an international, peer-reviewed forum which focuses on system-level research and development regarding aeronautics and astronautics. The journal emphasizes the unique role and increasing importance of informatics on aerospace. It fills a gap in current publishing coverage from outer space vehicles to atmospheric vehicles by highlighting interdisciplinary science, technology and engineering.
Potential topics include, but are not limited to:
Trans-space vehicle systems design and integration
Air vehicle systems
Space vehicle systems
Near-space vehicle systems
Aerospace robotics and unmanned system
Communication, navigation and surveillance
Aerodynamics and aircraft design
Dynamics and control
Aerospace propulsion
Avionics system
Opto-electronic system
Air traffic management
Earth observation
Deep space exploration
Bionic micro-aircraft/spacecraft
Intelligent sensing and Information fusion
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
