  Detection and identification of emitters provide vital information for
defensive strategies in electronic intelligence. Based on a received signal
containing pulses from an unknown number of emitters, this paper introduces an
unsupervised methodology for deinterleaving RADAR signals based on a
combination of clustering algorithms and optimal transport distances. The first
step involves separating the pulses with a clustering algorithm under the
constraint that the pulses of two different emitters cannot belong to the same
cluster. Then, as the emitters exhibit complex behavior and can be represented
by several clusters, we propose a hierarchical clustering algorithm based on an
optimal transport distance to merge these clusters. A variant is also
developed, capable of handling more complex signals. Finally, the proposed
methodology is evaluated on simulated data provided through a realistic
simulator. Results show that the proposed methods are capable of deinterleaving
complex RADAR signals.
