We address the problem of estimating the time delay between two versions of a signal, each embedded in ad-'ditive noise. A widely used time-delay estimator is the generalized cross correlator (GCC). Its performance was well studied and has been shown to be optimal for any signal-t-noise-ratio (SNR) when the signal and the two noise processes are uncorrelated Gaussians. In 8 non-Gauesian setting, we show, by means of Monte-Carlo simulations, that at low SNR a non-linear correlator with non-linearity which is matched to the noise distribution perform better then the hear correlator. At moderate SNR the preferred proGessor is a member of a family of time delay estimation (TDE) processors which are based on minimization of the norm of order E, of the difference between the two received signals. The achievable improvement increases as the distribution of the noise processes deviates from Gaussianity.
|Number of pages||3|
|State||Published - 1994|
|Event||7th IEEE SP Workshop on Statistical Signal and Array Processing, SSAP 1994 - Quebec, Canada|
Duration: 26 Jun 1994 → 29 Jun 1994
|Conference||7th IEEE SP Workshop on Statistical Signal and Array Processing, SSAP 1994|
|Period||26/06/94 → 29/06/94|