Robust estimation of highly-varying nonlinear instantaneous frequency of monocomponent signals using a lower-order complex-time distribution

• We propose a CTD for highly-varying IF estimation of monocomponent signals.
• We compare performance of the lower-order CTD with the WVD and two LCTDs.
• We evaluate its performance using simulations at different SNRs.
• The proposed CTD retains a high temporal resolution with robustness to noise.

This paper proposes an approach for robust estimation of highly-varying nonlinear instantaneous frequency (IF) in monocomponent nonstationary signals. The proposed method is based on a lower order complex-time distribution (CTD), derived by using the idea of complex-time differentiation of the instantaneous phase. Unlike other existing TFDs in the same framework, the proposed TFD is an order-free distribution which alleviates the subtractive cancellation error in IF estimation. The approach is applied to highly nonstationary monocomponent signals. Performance of the numerical implementation is compared with three existing IF estimation methods using three simulated signals. Noise analysis is also performed to evaluate the robustness of the method in presenfdece of additive noise at signal to noise ratio (SNR) varying from −10 dB to 20 dB. Results show that the proposed method outperforms the other methods at lower SNR and works reasonably well for the noiseless case.