Working modes recognition method of phased array radar based on TCN-BiLSTM parallel processing

Hongxing Wang; Zhengyun Jiang; Lushan Ding

doi:10.1117/12.2671073

28 April 2023 Working modes recognition method of phased array radar based on TCN-BiLSTM parallel processing

Hongxing Wang, Zhengyun Jiang, Lushan Ding

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126103A (2023) https://doi.org/10.1117/12.2671073
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

The variable signal patterns and extremely high data rate of phased array radar greatly increase the complexity of electromagnetic environment, which makes the traditional method of radar working mode identification face great challenges. In this paper, a network structure based on temporal convolutional network (TCN) and Bi-directional long short-term memory (Bi-LSTM) parallel fusion processing is proposed. Depending on the advantages of TCN in depth temporal feature extraction and Bi-LSTM in global time series feature extraction, the typical working mode of phased array radar is accurately recognized. The experimental results show that under the condition of complex parameter interleaving, the recognition accuracy of the network for typical operating modes of phased array radar reaches 96.77%, which proves the feasibility of the method.

Citation Download Citation

Hongxing Wang, Zhengyun Jiang, and Lushan Ding "Working modes recognition method of phased array radar based on TCN-BiLSTM parallel processing", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126103A (28 April 2023); https://doi.org/10.1117/12.2671073

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