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- W3035001878 abstract "Model order and frequency estimation of multiple 2-D complex sinusoids in additive white Gaussian noise are addressed. Frequency estimation follows the coarse-fine search strategy. Coarse estimates, obtained by locating maxima of the 2-D discrete Fourier transform, are refined in a two-stage procedure. In both stages, frequency refinement is based on three-point periodogram maximization. In order to provide accurate model order estimation (MOE) for a wide signal-to-noise ratio (SNR) range, our approach combines two metrics for sinusoid detection in the 2-D frequency domain, one for low and the other for high SNR values. The proposed frequency estimation method attains the Cramér-Rao lower bound and it outperforms parametric methods in terms of the estimation accuracy and numerical efficiency. Compared with information criterion-based methods, the proposed MOE approach is numerically more efficient, it does not require estimation of noise variance and hence does not suffer from overestimation at high SNR." @default.
- W3035001878 created "2020-06-19" @default.
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- W3035001878 date "2020-09-01" @default.
- W3035001878 modified "2023-10-16" @default.
- W3035001878 title "A low complexity model order and frequency estimation of multiple 2-D complex sinusoids" @default.
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- W3035001878 doi "https://doi.org/10.1016/j.dsp.2020.102794" @default.
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