High Resolution Spectral Estimation using BP via Compressive Sensing
In this paper we propose a method based on compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of sinusoids. In the case of finite-length signals, the Fourier coefficients are not exactly sparse due to the leakage effect if the frequency...
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| Outros Autores: | , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2015
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.19/2506 |
| País: | Portugal |
| Oai: | oai:repositorio.ipv.pt:10400.19/2506 |
| Resumo: | In this paper we propose a method based on compressed sensing (CS) for estimating the spectrum of a signal written as a linear combination of a small number of sinusoids. In the case of finite-length signals, the Fourier coefficients are not exactly sparse due to the leakage effect if the frequency is not a multiple of the fundamental frequency; To overcome this problem our algorithm transform the DFT basis into a frame with a larger number of vectors, by inserting columns between some of the initial ones. The algorithm applies Basis Pursuit (BP) to estimate the sinusoids amplitude, phase and frequency. |
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