Power spectral density of a signal with gaps?
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: