How do I calculate the power density spectrum if the measured phase has a constant drift?
Phase drift detrend with power density
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In some circumstances, it is not possible to synchronize Moku's onboard clock with the frequency synthesizer in the system, resulting in a constant drift in the measured phase trace. For example, the measured phase is dominated by a 1 Hz drift, obscuring the 1-degree phase modulation.
After the windowing process, the windowed time series almost maintains the shape of the Hann window because the linear drift is dominating.
When performing frequency spectra analysis on a signal with phase drift, the analysis can be dominated by spectral leakage from the drift component.
This spectral leakage caused by the drifting phase can be resolved by removing the trend in the measured phase. This allows the 1 Hz phase modulation to be seen in the calculated phase amplitude spectral density (ASD).
Comparing the detrended ASD with the non-detrended ASD shows that spectral leakage from the drifting phase obscures the actual phase modulations.
This can be fixed by a linear detrend process before the power spectrum density (PSD) calculation. In Python, the detrend can be performed by adding a detrend='constant' option in the scipy.signal.welch function. In MATLAB, a similar process can be done with a first-order detrend function, before the ASD calculation.