Dominant Frequency Peak Decreases with Increasing Window Size I have a signal that looks like this.



I analyse it using fast Fourier transforms to identify the frequency with the largest peak, which is always close to zero. (There are no other clear peaks.) If I use windows of different sizes (by "window" I mean size of the snippet I use – I don't know if this is the correct use of the terminology, however), the result shows that the dominant peak gets closer and closer to zero as the size of the windows increase. That is to say, if I plot 1/frequency against window size, it is linear. 

My initial thought is that if I had an infinitely long window, then the peak would be located at zero implying a DC offset, but the signal is centred on zero in an effort to avoid such an offset. Can someone explain why I see this phenomenon and how I can avoid it?

PS I even tried this using sliding windows so that I can get frequencies based on different parts of the data, but the issue persists.
Since your signal isn't sampled uniformly some strange things might happen when you apply FFT and look at the results.

What you should do is estimate the Uniform DFT of the Non Uniform Time Series.

One easy way to do it is use the reference code and analysis I posted on the question - Frequency Analysis of a Signal Without a Constant Sampling Frequency (Non Uniform Sampling in Time Domain).

Apply it on your data and things should behave more consistently.

One more thing, if you're after a peak, something which will make easier analyzing the data will be centering it. Namely make sure the samples have zero mean.