  Pulse-compression is a correlation-based measurement technique successfully
used in many NDE applications to increase the SNR in the presence of huge
noise, strong signal attenuation or when high excitation levels must be
avoided. In thermography, the pulse-compression approach was firstly introduced
in 2005 by Mulavesaala and co-workers, and then further developed by Mandelis
and co-authors that applied to thermography the concept of the thermal-wave
radar developed for photothermal measurements. Since then, many measurement
schemes and applications have been reported in the literature by several groups
by using various heating sources, coded excitation signals, and processing
algorithms. The variety of such techniques is known as pulse-compression
thermography or thermal-wave radar imaging. Even despite the continuous
improvement of these techniques during these years, the advantages of using a
correlation-based approach in thermography are still not fully exploited and
recognized by the community. This is because up to now the reconstructed
thermograms' time sequences after pulse-compression were affected by the
so-called sidelobes. This is a severe drawback since it hampers an easy
interpretation of the data and their comparison with other thermography
techniques. To overcome this issue and unleash the full potential of the
approach, this paper shows how it is possible to implement a pulse-compression
thermography procedure capable of suppressing any sidelobe by using a
pseudo-noise excitation and a proper processing algorithm.
