| Citation: | Hongguang LI, Ying GUO, Dongwei ZHANG, Yinsong YANG, Zisen QI, Ping SUI. Synchronous Frequency Hopping Signal Network Station Sorting Based on Underdetermined Blind Source Separation[J]. Journal of Electronics & Information Technology, 2021, 43(2): 319-328. doi: 10.11999/JEIT190920
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Considering the problem of synchronous Frequency Hopping(FH) network station sorting, an Underdetermined Blind Source Separation(UBSS) algorithm based on time-frequency domain single source point detection is proposed. Firstly, the algorithm performs time-frequency transform on the observed signal, and uses adaptive threshold denoising algorithm to eliminate the background noise of the time-frequency matrix. It can increase the algorithm anti-noise performance. Then, single source point detection is performed according to the absolute azimuth difference of the signal. It can effectively ensure the sufficient sparsity of a single source point. The hybrid matrix estimation is completed by the improved fuzzy C value clustering algorithm. It can reduce the influence of noise and sample set distribution differences and improve the estimation accuracy. Finally, the source signal is reconstructed and restored by a variable step size Sparsity Adaptive Subspace Pursuit(SASP) algorithm. The simulation experiments show that the proposed algorithm has higher recovery accuracy of the frequency hopping signal under the condition of low Signal to Noise Ratio (SNR), and can effectively complete the blind separation of the synchronous frequency hopping signal.
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