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.

Answers


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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