Zhong Ye, E. Satorius, V. Vilnrotter, T. Pham, D. Fort
{"title":"Large antenna array techniques for very low SNR channels","authors":"Zhong Ye, E. Satorius, V. Vilnrotter, T. Pham, D. Fort","doi":"10.1109/MILCOM.2001.986062","DOIUrl":null,"url":null,"abstract":"Various arraying techniques are studied focusing on the very low received signal SNR channel conditions commonly found in deep space communications applications. These include correlation-based blind approaches as well as a sub-space based superresolution approach. In addition to weak received signals, atmospheric turbulence and spatially correlated interference from nearby planets (and possibly quasars) creates additional channel impairment. It is demonstrated that the sub-space based MUSIC algorithm is a strong candidate for this application that can provide great angle separation accuracy and interference suppression capability. Adaptive beamforming techniques in combination with the MUSIC algorithm provide a flexible platform to combat channel impairment.","PeriodicalId":136537,"journal":{"name":"2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MILCOM.2001.986062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Various arraying techniques are studied focusing on the very low received signal SNR channel conditions commonly found in deep space communications applications. These include correlation-based blind approaches as well as a sub-space based superresolution approach. In addition to weak received signals, atmospheric turbulence and spatially correlated interference from nearby planets (and possibly quasars) creates additional channel impairment. It is demonstrated that the sub-space based MUSIC algorithm is a strong candidate for this application that can provide great angle separation accuracy and interference suppression capability. Adaptive beamforming techniques in combination with the MUSIC algorithm provide a flexible platform to combat channel impairment.