I have looked at previous questions on this topic but I am still unsatisfied. I want to predict how accurately I can estimate the phase of a tone as a function of signal SNR, tone frequency, and the signal length (assuming AWGN). My method for estimation is to just do the FFT, pick the tone frequency and calculate the angle of the phasor.
Initial Guess
My initial hypothesis was that the accuracy would depend on the contrast between the tone and the noise floor in the power spectral density (PSD). Essentially, this contrast would act as the "SNR" for my phase measurement.
Back-of-the-Envelope Calculation
Let's denote the contrast in the PSD as $ SNR_f = \frac{S_f}{N_f} $.
$ S_f $ is proportional to the variance of the signal, $ S_f \propto \text{var(sig)} $.
The noise under the PSD peak, $ N_f $, is proportional to $ \frac{\text{var(noise)}}{B_{\text{noise}}} \times B_{\text{sig}} = \eta \times B_{\text{sig}} $, where $ \eta $ is the noise spectral density. Let's assume that the estimation is done using only one FFT bin, so $ B_{\text{sig}} \propto \frac{1}{T} $.
Thus, we have:
$$ SNR_f \propto \frac{\text{var(sig)}}{\eta} \times T $$
Problem
What bothers me is that according to this formula, the accuracy of the phase estimation seems unaffected by the frequency of the tone—given a fixed SNR and signal length. Intuitively, it feels like having more cycles in the time window should make the phase easier to estimate. Am I missing something fundamental here?
Questions
Can someone provide an intuitive explanation for what I should expect?
Bonus: Is there a method more accurate or computationally efficient than FFT for phase estimation of a tone?