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Identification of Radar Emitter Type with Recurrent Neural Networks

: Apfeld, S.; Charlish, A.; Ascheid, G.


Davies, M.:
Sensor Signal Processing for Defence Conference (SSPD) 2020 : SSPD online : virtual conference, 15th and 16th September 2020
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-72813-810-7
ISBN: 978-1-72813-811-4
ISBN: 978-1-7281-3810-7
ISBN: 978-1-7281-3811-4
Sensor Signal Processing for Defence Conference (SSPD) <9, 2020, Online>
Fraunhofer FKIE ()

In this paper, we present a method for the identification of different multifunction radar emitter types. It is based on Long Short-Term Memory recurrent neural networks and a previously published hierarchical modelling approach. This approach maps radar pulses to different levels of symbols which can be regarded as parts of a radar language. We evaluate our method with an example emitter that can make use of three different resource management techniques. The results show that it is possible to distinguish between radar types that mainly use the same emission parameters but differ in the resource management method.