engleski

Multicomponent Noisy Signal Adaptive Instantaneous Frequency Estimation Using Components Time Support Information

This paper proposes an adaptive method for components instantaneous frequency (IF) estimation of noisy nonstationary multicomponent signals, combined with the components time support estimation method based on the short-time Renyi entropy (STRE). Components localization and separation are done using a double-direction component tracking and extraction method presented in this paper, while the IF estimation is done using the adaptive algorithms based on the intersection of confidence intervals (ICI) rule and the relative intersection of confidence intervals (RICI) rule. The results obtained using the ICI and RICI rules are compared for various window types, SNRs, and time-frequency distributions (TFDs), both with and without using the information on components time support. Most of the error in IF estimation using the ICI and RICI based methods is caused by imprecise components time support estimation. The proposed methods combined with the STRE have achieved a significant accuracy improvement in terms of the mean absolute error (MAE) and the mean squared error (MSE), reducing them by up to 73% and 93%, respectively. The method has been applied to real-life signals and proven to be an efficient tool for IF estimation of noisy nonstationary multicomponent signals.

multicomponent signal; instantaneous frequency (IF) estimation; short-time Renyi entropy (STRE); component time support estimation; time-frequency distributions

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