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- Title
Intra-pulse modulation recognition of radar signals based on multi-feature random matching fusion network.
- Authors
Liao, Yanping; Jiang, Fan; Wang, Jinli
- Abstract
Intra-pulse modulation recognition of radar signals plays an important role in the field of electronic warfare. In this paper, a multi-feature random matching fusion (MFRMF) network is proposed to deal with the recognition technology of radar signals' intra-pulse modulation at a low signal-to-noise ratio (SNR). First, we extract 12 traditional parameter features of radar signals and screen out 7 more important features. Next, we analyze and extract the Time–frequency images. Finally, the MFRMF network with the idea of residual learning, self-attention mechanism, and random matching algorithm is adopted to perform feature learning and identify the intra-pulse modulation type of radar signals. Simulation results demonstrate that MFRMF can effectively reduce the interference of noise on signal classification and improve recognition accuracy at a low SNR. It can classify 10 kinds of radar signals, and the overall recognition accuracy achieves 90.6% and 95.4% when the SNR is − 8 dB and − 6 dB, respectively.
- Subjects
MILITARY electronics; SIGNAL classification; SIGNAL-to-noise ratio; TIME-frequency analysis
- Publication
Journal of Supercomputing, 2023, Vol 79, Issue 6, p6422
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-022-04902-9