2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015
DOI: 10.1109/icassp.2015.7178576
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Universal lower bounds on sampling rates for covariance estimation

Abstract: Abstract-Covariance estimation from compressive samples has become particularly attractive for two main reasons. First, many applications do not require the signal itself, and secondorder statistics are oftentimes sufficient. The resulting requirement on the sampling rate of the original signal can therefore be reduced. Second, signal recovery from compressive samples leads to underdetermined systems which require additional constraints, such as the popular sparsity assumption. In contrast, covariance estimati… Show more

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Cited by 2 publications
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“…This performance improvement is primarily due to the fact that the difference coarray constructed from the array with arbitrary physical locations has more DoF than the regular nested array. A similar concept was considered in [68], where temporal off-the-Nyquist-grid sampling is introduced, which yields more lags or differences for covariance estimation. And as before, Known PS provides better DoA estimates than Unknown PS yet with a small gap.…”
Section: Doa Estimation With Arbitrary Arraysmentioning
confidence: 99%
“…This performance improvement is primarily due to the fact that the difference coarray constructed from the array with arbitrary physical locations has more DoF than the regular nested array. A similar concept was considered in [68], where temporal off-the-Nyquist-grid sampling is introduced, which yields more lags or differences for covariance estimation. And as before, Known PS provides better DoA estimates than Unknown PS yet with a small gap.…”
Section: Doa Estimation With Arbitrary Arraysmentioning
confidence: 99%