Detection and parameter estimation of multiple nonGaussian sources via higher order statistics

Simultaneous detection of signal arriving at a sensor array and estimation of their parameters is carried out using higher than second-order statistics. Information theoretic criteria which are (at least theoretically) insensitive to additive Gaussian noise are developed to estimate consistently the...

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Veröffentlicht in:IEEE transactions on signal processing 1994-05, Vol.42 (5), p.1145-1155
Hauptverfasser: Shamsunder, S., Giannakis, G.B.
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description Simultaneous detection of signal arriving at a sensor array and estimation of their parameters is carried out using higher than second-order statistics. Information theoretic criteria which are (at least theoretically) insensitive to additive Gaussian noise are developed to estimate consistently the parameters as well as the number of non-Gaussian but unknown sources. The novel cumulant based algorithms can estimate parameters of more sources with fewer sensors. Simulations confirm superior resolution capability of the proposed methods for both narrow-band and wideband sources in the presence of low SNR additive correlated Gaussian noise.< >
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subjects Additive noise
Applied sciences
Array signal processing
Colored noise
Direction of arrival estimation
Exact sciences and technology
Gaussian noise
Higher order statistics
Parameter estimation
Radiolocalization and radionavigation
Sensor arrays
Signal processing
Signal processing algorithms
Telecommunications
Telecommunications and information theory
title Detection and parameter estimation of multiple nonGaussian sources via higher order statistics
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