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학술지 Spectral Domain Noise Modeling in Compressive Sensing-Based Tonal Signal Detection
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후천린, 김진영, 최승호, 김창주
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, v.E98-A no.5, pp.1122-1125
일본, 전자정보통신학회 (IEICE)
Tonal signals are shown as spectral peaks in the frequency domain. When the number of spectral peaks is small and the spectral signal is sparse, Compressive Sensing (CS) can be adopted to locate the peaks with a low-cost sensing system. In the CS scheme, a time domain signal is modelled as y = 過F-1s, where y and s are signal vectors in the time and frequency domains. In addition, F-1 and 過 are an inverse DFT matrix and a random-sampling matrix, respectively. For a given y and 過, the CS method attempts to estimate s with l0 or l1 optimization. To generate the peak candidates, we adopt the frequency-domain information of 큄 = Fy, where y is the extended version of y and y (n) is zero when n is not elements of CS time instances. In this paper, we develop Gaussian statistics of 큄. That is, the variance and the mean values of 큄 (k) are examined.
KSP 제안 키워드
CS method, CS scheme, Compressive sensing, DFT matrix, Gaussian statistics, Low-cost, Mean values, Sampling matrix, Sensing system, Spectral peaks, frequency domain(FD)