On the detection of non-stationary signals in the matched signal transform domain

Andrei Anghel (1, 2) , Gabriel Vasile (2) , Cornel Ioana (2) , Remus Cacoveanu (1) , Silviu Ciochina (1)

1 UPB - University Politehnica of Bucharest [Romania]
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

This paper proposes a detector of multi-component non-stationary signals based on the matched signal transform (MST). In the MST domain, a non-stationary signal is localized at its frequency modulation rate with the transform's basis modulation function. The MST can be numerically implemented either as a freestanding discrete version of an integral transform, or for faster computation, as a time resampled version of the original signal followed by a fast Fourier transform. We analyze the noise statistics in the MST domain and derive the analytical forms of the probability density function for both implementations, considering the non-stationary signal embedded in white Gaussian noise. We propose a detector based on the squared magnitude of the MST and show how its detection performances depend on the chosen implementation. All the theoretical derivations are validated through Monte Carlo simulations.

Domaines: Traitement du signal et de l'image [eess.SP]

Andrei Anghel, Gabriel Vasile, Cornel Ioana, Remus Cacoveanu, Silviu Ciochina. On the detection of non-stationary signals in the matched signal transform domain. ICASSP 2016 - 41st IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2016, Shanghai, China. pp.4204-4208, ⟨10.1109/ICASSP.2016.7472469⟩. ⟨hal-01324109⟩