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White Why do we use white noise to estimate echoes?

I'm interested in the case where aI have received a signal as a composition of three echoes of the transmitted signal x[n] $x[n]$ (each echo has its amplitude and time delay). I know that in order to compare the signals I use cross-correlation. My question is if I use rxx[m] = delta[m]$r_{xx}[m] = \delta[m]$, would that make it easier to calculate the parameters of echoes? And, if so, can you explain me why?

White do we use white noise to estimate echoes?

I'm in the case where a have received a signal as a composition of three echoes of the transmitted signal x[n] (each echo has its amplitude and time delay). I know that in order to compare the signals I use cross-correlation. My question is if I use rxx[m] = delta[m], would make it easier to calculate the parameters of echoes? And if so can you explain me why?

Why do we use white noise to estimate echoes?

I'm interested in the case where I have received a signal as a composition of three echoes of the transmitted signal $x[n]$ (each echo has its amplitude and time delay). I know that in order to compare the signals I use cross-correlation. My question is if I use $r_{xx}[m] = \delta[m]$, would that make it easier to calculate the parameters of echoes? And, if so, can you explain me why?

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Jona
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White do we use white noise to estimate echoes?

I'm in the case where a have received a signal as a composition of three echoes of the transmitted signal x[n] (each echo has its amplitude and time delay). I know that in order to compare the signals I use cross-correlation. My question is if I use rxx[m] = delta[m], would make it easier to calculate the parameters of echoes? And if so can you explain me why?