  Although radar and communications signal classification are usually treated
separately, they share similar characteristics, and methods applied in one
domain can be potentially applied in the other. We propose a simple and unified
scheme for the classification of radar and communications signals using Long
Short-Term Memory (LSTM) neural networks. This proposal provides an improvement
of the state of the art on radar signals where LSTM models are starting to be
applied within schemes of higher complexity. To date, there is no standard
public dataset for radar signals. Therefore, we propose DeepRadar2022, a radar
dataset used in our systematic evaluations that is available publicly and will
facilitate a standard comparison between methods.
