  Detection of a signal hidden by noise within a time series is an important
problem in many astronomical searches, i.e. for light curves containing the
contributions of periodic/semi-periodic components due to rotating objects and
all other astrophysical time-dependent phenomena. One of the most popular tools
for use in such studies is the "periodogram", whose use in an astronomical
context is often not trivial. The "optimal" statistical properties of the
periodogram are lost in the case of irregular sampling of signals, which is a
common situation in astronomical experiments. Parts of these properties are
recovered by the "Lomb-Scargle" (LS) technique, but at the price of theoretical
difficulties, that can make its use unclear, and of algorithms that require the
development of dedicated software if a fast implementation is necessary. Such
problems would be irrelevant if the LS periodogram could be used to
significantly improve the results obtained by approximated but simpler
techniques. In this work we show that in many astronomical applications simpler
techniques provide results similar to those obtainable with the LS periodogram.
The meaning of the "Nyquist frequency" is also discussed in the case of
irregular sampling.
