基于长短时记忆网络的雷达波形设计

doi:10.12305/j.issn.1001-506X.2021.02.12

Abstract

Abstract:

Considering the problem that the waveform designed using single-criterion is difficult to meet the radar's multi-working mode and multi-tasking, a waveform design method based on long short-term memory (LSTM) network is proposed, through combining mutual information (MI) criterion and signal to clutter and noise ratio (SCNR) criterion. Firstly, a LSTM network composed of input layer, LSTM layer, and output layer is designed. Secondly, a train set composed of signals generated through MI criteria and SCNR criteria and the corresponding environmental information is constructed, which is used to train the LSTM network. Finally, the trained LSTM network is used to design waveform, and the radar performance of the waveform generated by the proposed method is compared with the single-criterion design waveform. In order to measure the comprehensive performance of radar, a novel comprehensive performance indicator and target recognition rate of radar are proposed. Simulation results show that when the signal generated by the proposed method is used as the transmit signal, the comprehensive performance of radar is increased by 0.67% on average compared with MI criterion and 1.47% compared with SCNR criterion. It is proved that the proposed method can combine the advantages of the MI criterion and SCNR criterion, and improve the comprehensive performance of radar.

Key words: waveform design, mutual information (MI) criterion, signal to clutter and noise ratio (SCNR) criterion, long short-term memory network (LSTM)

CLC Number:

TN951

Junlong ZHAO, Wei LI, Honglin WANG, Teng HUANG, Yifu GAN, Ye WANG. Waveform design of radar based on long short-term memory network[J]. Systems Engineering and Electronics, 2021, 43(2): 376-382.

Figures/Tables 9

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类型	P_d	P_r	P_c
LSTM网络	0.444 3	0.968 7	0.430 4
MI准则	0.423 7	1.000 0	0.423 7
SCNR准则	0.568 4	0.731 4	0.415 7

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