M. Barjenbruch, Franz Gritschneder, K. Dietmayer, J. Klappstein, J. Dickmann
{"title":"Memory efficient spectral estimation on parallel computing architectures","authors":"M. Barjenbruch, Franz Gritschneder, K. Dietmayer, J. Klappstein, J. Dickmann","doi":"10.1109/DSP-SPE.2015.7369576","DOIUrl":null,"url":null,"abstract":"A method for spectral estimation is proposed. It is based on the multidimensional extensions of the RELAX algorithm. The fast Fourier transform is replaced by multiple Chirp-Z transforms. Each transform has a much shorter length than the transform in the original algorithm. This reduces the memory requirements significantly. At the same time a high degree of parallelism is preserved. A detailed analysis of the computational requirements is given. Finally, the proposed method is applied to automotive radar measurements. It is shown, that the multidimensional spectral estimation resolves multiple scattering centers on an extended object.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"12 1","pages":"337-340"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","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.2015.7369576","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A method for spectral estimation is proposed. It is based on the multidimensional extensions of the RELAX algorithm. The fast Fourier transform is replaced by multiple Chirp-Z transforms. Each transform has a much shorter length than the transform in the original algorithm. This reduces the memory requirements significantly. At the same time a high degree of parallelism is preserved. A detailed analysis of the computational requirements is given. Finally, the proposed method is applied to automotive radar measurements. It is shown, that the multidimensional spectral estimation resolves multiple scattering centers on an extended object.
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