Journal of System Simulation
Abstract
Abstract: Aiming at the problem that traditional recognition methods of radar emitter signal have low accuracy in low signal to noise ratio (SNR) environment, and are usually suitable for only several specific radar signals, an identification approach of radar signal based on distance features is proposed. Several cluster centers are extracted via the k-means algorithm, and the Dynamic Time Warping (DTW) values between the radar signal and the cluster center are calculated respectively, which are combined as the input features of k-Nearest Neighbor (k-NN) algorithm. The simulation results show that when the SNR is 3 dB, the identification rate of the 6 classes of radar signals is 91%. Compared to the method based on wavelet ridge-frequency cascade-feature, the proposed method also shows better recognition performance.
Recommended Citation
Huang, Yingkun; Jin, Weidong; Kang, Yan; and Zhu, Jiehao
(2022)
"Radar Emitter Signal Identification Via Distance Features,"
Journal of System Simulation: Vol. 33:
Iss.
12, Article 20.
DOI: 10.16182/j.issn1004731x.joss.21-FZ0808
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol33/iss12/20
First Page
2959
Revised Date
2021-08-11
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-FZ0808
Last Page
2966
CLC
TP391.9
Recommended Citation
Huang Yingkun, Jin Weidong, Yan Kang, Zhu Jiehao. Radar Emitter Signal Identification Via Distance Features[J]. Journal of System Simulation, 2021, 33(12): 2959-2966.
DOI
10.16182/j.issn1004731x.joss.21-FZ0808
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