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Impulsive noise is commonly present in many applications of actual communication networks, leading to algorithms based on the Gaussian model no longer being applicable. A robust parameter estimator of frequency-hopping (FH) signals suitable for various impulsive noise environments, referred to as ℓp-STFT, is proposed. The ℓp-STFT estimator replaces the ℓ2-norm by using the generalized version ℓp-norm where 1 &lt; p &lt; 2 for the derivation of the short-time Fourier transform (STFT) as an objective function. It combines impulsive noise processing with any time-frequency analysis algorithm based on STFT. Considering the accuracy of parameter estimation, the double-window spectrogram difference (DWSD) algorithm is used to illustrate the suitability of ℓp-STFT. Computer simulations are mainly conducted in α-stable noise to compare the performance of ℓp-STFT with STFT and fractional low-order STFT (FLOSTFT), Cauchy noise, and Gaussian mixture noise as supplements of different background noises to better demonstrate the robustness and accuracy of ℓp-STFT.

ℓp-STFT: A Robust Parameter Estimator of a Frequency Hopping Signal for Impulsive Noise