Does anyone know if it is possible to find a power spectral density of a signal with gaps in it. For example (in matlab syntax cause that is what I'm familiar with)
ta=1:1000;
tb=1200:3000;
t=[ta tb]; % this is the timebase
signal=randn(size(t)); this is a signal
figure(101)
plot(t,signal,'.')
I'd like to be able to determine frequencies on a longer time base that just the individual sections of data. Obviously I could just take the PSD of individual sections but that will limit the lowest frequency. I could interpolate the data, but this would colour the PSD.
Any thoughts would be much appreciated.
The Lomb-Scargle periodogram algorithm is usually used to perform analysis on unevenly spaced data (sampled at arbitrary time points) or when a proportion of the data is missing.
Here's a couple of MATLAB implementations:
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