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

Abstract

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 < p < 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.