I am working on using Welch's method (https://www.osti.gov/servlets/purl/5688766/) to estimate a Power Spectral Density (PSD). This algorithm involves scaling a set of averaged FFTs by the equivalent noise bandwidth (ENBW) or the sum of the coefficients a window function applied to the time domain signal, to arrive at an estimate of the PSD. In the examples I've reviewed thus far, the coefficients of the windowing function provide the means for estimating the PD
In my system, I also want to implement a low-pass, antialiasing, FIR filter on the input data. To first-order, I use a specific window (e.g. Blackman, Hamming) to truncate the ideal, infinite impulse response of the anti-aliasing filter. In the link I shared before, the windowing function provides both a means of estimating ENBW and limiting spectral leakage, however anti aliasing filters are not discussed.
- Can I estimate the ENBW of the FIR filter or W as the coefficients of the window function I use in designing my FIR filter? Do I need to additionally compensate for the FIR filter?
- If I do need to additionally adjust my estimate of W or ENBW due to the transfer function of the FIR filter (anti aliasing & window), how should I do so?