Frequency Modulation Recognition for Radar Signal 
based on Resnet-LSTM Network

Xuying Zhang*; Yang Liu; Xinwen Yan; Longbiao Hu; Guoyuan Chang

Frequency Modulation Recognition for Radar Signal based on Resnet-LSTM Network

Xuying Zhang*, Yang Liu, Xinwen Yan, Longbiao Hu, Guoyuan Chang

Abstract

In order to satisfy the modulation recognition requirements for radar signal with large scale changes in pulse-width and bandwidth,
the Resnet-LSTM network is proposed in this paper. First, the waveform is preprocessed by self-correlation, and then the I/Q waveform and
self-correlation result are as the network input. Secondly, the local characteristics were extracted by Resnet network; and lastly the LSTM
network is adopted to extract the serialization representation. The proposed algorithm avoids the flaw of CNN network cannot adapt to variable length, and problem of memory forgetting of the LSTM network for long sequence is reduced. The simulation shows that the modulation
recognition accuracy is more than 96.1% over the detection sensitivity for LFM, Parabolic-NLFM, Triangular-NLFM, Sine-NLFM, Sawtooth-NLFM and FSK signals.

Keywords

Large scale changes; Self-correlation; Resnet-LSTM network

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References

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