{"title":"Subspace smearing and interference mitigation with array radio telescopes","authors":"G. Hellbourg","doi":"10.1109/DSP-SPE.2015.7369566","DOIUrl":null,"url":null,"abstract":"Array radio telescopes are suitable for the implementation of spatial filters. These filters present the advantage of canceling potential radio frequency interference (RFI) while recovering uncorrupted Time-Frequency data, of interest to astronomers. Although information regarding the sources of RFI can be a priori known or reliably inferred, the complexity of radio telescope systems randomizes the formulation of the subspace spanned by the RFI due to a lack of calibration or characterization. This knowledge is however necessary for building an efficient spatial filter, and needs therefore to be estimated.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"78 1","pages":"278-282"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSP-SPE.2015.7369566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Array radio telescopes are suitable for the implementation of spatial filters. These filters present the advantage of canceling potential radio frequency interference (RFI) while recovering uncorrupted Time-Frequency data, of interest to astronomers. Although information regarding the sources of RFI can be a priori known or reliably inferred, the complexity of radio telescope systems randomizes the formulation of the subspace spanned by the RFI due to a lack of calibration or characterization. This knowledge is however necessary for building an efficient spatial filter, and needs therefore to be estimated.