I have some signal which I have measured N different times and I want to calculate the noise power spectrum of it. Intuitively to me the way I would do this is simply calculating the power spectrum of the noise. To do this I would take the magnitude square of the fourier transform of the auto covariance of the standard deviation over my N different trials. That is a bit of a mouthful so I'll try to clarify what I mean. First I want to get the noise from my N repeated measurements, so I take the standard deviation over the N measurements and estimate this as my "noise waveform". Then to calculate the power spectrum I do the usual routine which is by taking the fourier transform of the autocovariance, and squaring the result.
This seems intuitive to me, however I can't find any text books or journal articles that confirm my intuition, so I'm left being a bit confused about whether this is really the right technique or not. Could anyone shed any light on the matter if they have experience with this?