I am working on some experimental data which, at some point, need to be time-integrated and then high-pass filtered (to remove low frequency disturbancies introduced by integration and unwanted DC component).
The aim of my work is not related to filtering, but still I would like to analyze more in detail the filters I am using to give some justification (for example to motivate why I chosed to use a 4th order filter instead of a higher/lower one).
This is the filter I am using:
delta_t = 1.53846e-04; Fs = 1/delta_t; cut_F = 8; Wn = cut_F/(Fs/2); ftype = 'high'; [b,a] = butter(4,Wn,ftype); filtered_signal = filtfilt(b,a,signal);
I already had a look here: https://stackoverflow.com/questions/5591278/high-pass-filtering-in-matlab to learn something about filters (I never had a course on signal processing) and I used
to see the impulse response, step response ecc. of the filter I have used.
The problem is that I do not know how to "read" these plots.
What do I have to look for?
How can I understand if a filter is good or not? (I do not have any specification about filter performances, I just know that the lowest frequency I can admit is 5 Hz)
What features of different filters are useful to be compared to motivate the choice?
For example, what info can I see plotting the round-off noise power spectrum of 2 different filters?(high pass Butterworth of different orders: 4 and 22)
I tried decimating the signal to reduce the sampling frequency as suggested in the comments and this is what I get
The green one is the new filter's round off noise spectrum having reduced the sampling frequency (now = 325 Hz), the blue one is the older with sampling frequency = 6.5 kHz.
Things look a bit better but still not good enough, am I right?